@article{ 
author = {Mahmoodi, Maryam Sadat},  
title = {Designing a Heart Disease prediction System using Support Vector Machine}, 
abstract ={Introduction: Cardiovascular diseases are the leading cause of death worldwide. The world health Organization has estimated 12 million deaths per year worldwide, due to the cardiovascular diseases. The main aim of this study was to design a smart computer-aided system for the diagnosis of heart disease in patients. Methods: In this study descriptive and analytical study, data of 270 people with 13 features were used. The fuzzy system and support vector machine classifier were combined using facilities of MATLAB software and were simulated by a system of core i5 and windows7, as the operating system, to diagnose patients with heart disease. Results: Fuzzy technique and support vector machine algorithm that were used for the diagnosis of heart disease was efficient in rapid diagnosis and consequently increasing the patient chance for survival. Evaluation criteria in this system were rates of categorization and sensitivity and the system performance for these two indicators were respectively  85% and 85.8%. Conclusion: According to the results, the proposed system can diagnose patients with cardiovascular diseases with a relatively high accuracy.  },  
Keywords = {Cardiovascular Disease, Fuzzy System, Support Vector Machine Classifier},
volume = {4},
Number = {1}, 
pages = {1-10}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-182-en.html},  
eprint = {http://jhbmi.ir/article-1-182-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Sheikhtaheri, Abbas and Ghandali, Fatemeh and ZamaniGhaletaki, Gholamrez},  
title = {Determination of the Required Educational Content in the Development of Educational Mobile Application for Patients with Epilepsy: Perspectives of Patients and Physicians}, 
abstract ={Introduction: Epilepsy is a common chronic neurological disease. In epilepsy treatment process, both of appropriate treatment options and patient education should be considered. Nowadays, mobile technologies have been known as a proper platform for improvement of patients’ knowledge in chronic diseases. The aim of this study was to assess the perspectives of epileptic patients and physicians about the required educational content in developing an educational mobile application for epilepsy. Methods: In this cross-sectional study, the perspectives of 100 patients with epilepsy who were members of the Iranian Epilepsy Association and 15 physicians who were members or colleagues of this association were surveyed about the patients’ educational needs. The applied questionnaire included 19 questions in three areas (disease information, lifestyle and used medications). Data were analyzed by the use of descriptive statistics (mean and standard deviation).   Results: A variety of  items such as first aid, cause, symptoms, complications and treatment of epilepsy, the effect of exercise, sleep, driving, occupation, marriage, pregnancy, nutrition in epilepsy, information about antiepileptic drugs and their complications, and the importance of the regular use of medications should be considered in the educational content of the application. Conclusion: This study indicates that the educational content for developing a mobile application for patients with epilepsy from the perspectives of patients and physicians includes three domains of life style, disease information and medication. Totally, 15 educational requirements were identified that should be considered in developing the application.  },  
Keywords = {Epilepsy, Educational needs, Patient, Physician, Mobile apps},
volume = {4},
Number = {1}, 
pages = {11-20}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-192-en.html},  
eprint = {http://jhbmi.ir/article-1-192-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Zabbah, Iman and YasrebiNaeini, Seyed Ehsan and Ramazanpoor, Zahra and Sahragard, Khadije},  
title = {The Diagnosis of Thyroid Diseases Using Combinati on of Neural Networks through Hierarchical Method}, 
abstract ={Introduction: Problems in thyroid gland are more common than in other glands of human body, and if they are not diagnosed early, thyroid storm or myxedema coma is likely to happen that might lead to death; therefore, on-time diagnosis of thyroid disorders (Hypothyroidism or hyperthyroidism) based on Laboratory and clinical tests is necessary. The main object of this research was to present a model based on data mining techniques that is capable of predicting thyroid diseases. Methods: This study was a descriptive-analytic study and its database included 7200 independent records based on 21 risk factors derived from UCI data reference. From all records, 70% were used for training and 30% for testing. First, neural networks performance was reviewed in order to diagnose thyroid diseases, and then an algorithm for combination of neural networks through hierarchical method was presented. Results: After modeling and comparing the generated models and recording the results, accuracies of predicting thyroid disorders using neural network and hierarchical method were found to be 96.6% and 100% respectively. Conclusion: Reducing misdiagnosis of thyroid diseases has always been one of the most important aims of researchers. Using methods based on data mining can decrease these errors. This study showed that using combination of neural networks through hierarchical method improves diagnosis accuracy.},  
Keywords = {Artificial neural network, MLP network, Combination of neural networks, Thyroid diagnosis},
volume = {4},
Number = {1}, 
pages = {21-31}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-187-en.html},  
eprint = {http://jhbmi.ir/article-1-187-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Mehrolhassani, Mohammad Hosein and Vali, Leila and Moein, Hamid and Ghanbarnejad, Mahtab},  
title = {The Analysis of the Quality of Patient Drug Information Recording Process at Referral Teaching Hospital Using Six Sigma}, 
abstract ={Introduction: Sharp rise in health care costs associated with the reduction of hospitals' support by government has increased the importance of insurance organizations as the main source of hospitals' income. An important part of hospitals’ demands is related to the medical records of Iranian Health Insurance organization that are subject to deductions and are deduced from the hospitals’ demands after investigating the cause of defect in the process. Methods: The present study was conducted as a retrospective descriptive research. In this study, sampling was not conducted and all incomplete files of patients covered by Iranian Health Insurance Organization in the reference hospital (n=30) were entered into the study. Data of checklists were entered into Excel software version 22 and the causes were determined by using Fishbone diagram. Six-sigma scale was used to analyze the quality of the process. Results: Process errors were detected in 6 groups and the highest error rates were respectively related to pharmaceutical orders control stages, entering them in cards and requesting drug through drug delivering system. The quality of the reviewed process was evaluated as moderate level based on the calculated sigma. The highest rate of error was related to the records of patients covered by rural fund of non-global services. Conclusion: Measures such as staff training, monitoring and updating the record keeping system and improving external parts coordination can greatly reduce errors in three above-mentioned stages.  },  
Keywords = {Process, Drug information, Six Sigma, Deductions        },
volume = {4},
Number = {1}, 
pages = {32-38}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-178-en.html},  
eprint = {http://jhbmi.ir/article-1-178-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Ghasemzadeh, Foroughosadat and Arab-kheradmand, Ali and Daklan, Soroush and Shabaninezhad, Alireza and Garajei, Ata and Etminani, Kobr},  
title = {Determination of the Most Important Factors Affecting Non-Melanoma Skin Cancer Using Data Mining Algorithms}, 
abstract ={Introduction: Non-melanoma skin cancer (NMSC) has recently been one of the three most common cancers in Iran. Inappropriate management of the disease has led to an increase in the prevalence and overhead costs. Data mining techniques are helpful in the analysis of patient records and accurate management of diseases. This study aimed to find hidden patterns and relationships in the data of NMSC patients using data mining algorithms. Methods: In this applied study, study population consisted of medical records of 828 NMSC patients referred to the Cancer Institute of Imam Khomeini Hospital in Tehran during 2006-2015. Demographic variables and NMSC risk factors were clustered using K-Means algorithm. Apriori algorithm was applied as well for extraction of association rules and determination of patient’s common information with a confidence of ≥ 0.9. Results: According to the studied variables, NMSC patients were classified in four clusters and three important factors influencing the disease were identified as abnormal BMI, high risk occupations and previous history of cancer. Seven rules were approved by association rules and the highest associations were found between the past history of the disease, the involved site, the relapse, and the type of NMSC. Conclusion: For the first time, this study could highlight the most important factors affecting NMSC using data mining methods. These factors should be considered either in self examination or screening skin tests in high-risk groups. In future studies, the contribution of physiological, ecological and genetic factors in the development of skin cancer should be jointly investigated as well.  },  
Keywords = {Non-Melanoma Skin Cancer, Data Mining, Clustering, Association rules, Risk Factor},
volume = {4},
Number = {1}, 
pages = {39-47}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-204-en.html},  
eprint = {http://jhbmi.ir/article-1-204-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Zeinali, Nahid and Asosheh, Abbas and Setareh, Soug},  
title = {Provide Interoperability Model to Interact in Hospital Information Systems}, 
abstract ={Introduction: The arrival of diverse and disparate hospital information systems by different-brands, on various platforms in the field of electronic health, has led to problems of interoperability. Interoperability is defined as the ability for two (or more) systems or components to exchange information and to use the information that has been exchanged. This paper aims to provide the hospital information system interoperability model. Provided that it cover all aspects of the interoperability. Method: This study is an applied- descriptive. The study includes three phase, at first required indicators to achieve all aspects of interoperability in hospital information system will be identified. In the following, provide the hospital information system interoperability model. Finally, this model with using a scenario based on a software architecture analysis method will be evaluated. Results: In this study, in order to achieve complete interoperability in Hospital Information System has been used a HSB approach. The presented model has necessary indicators for achieving all levels of interoperability (Technical, syntactic, semantic and organizational). EHealth experts confirmed this model using with architecture trade-off analysis method (ATAM). Conclusion: Achieving interoperability in healthcare information systems due to the complexity, diversity and standards is very difficult. And this challenges include technical, syntactic, semantic organizational. Increasing degree of interoperability and compatibility between hospital information systems cause to facilitate cooperation system together and increase efficiency, clinical performance and management of this systems.  },  
Keywords = {Interoperability, Hospital Information System, E-health},
volume = {4},
Number = {1}, 
pages = {48-58}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-205-en.html},  
eprint = {http://jhbmi.ir/article-1-205-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Mirsharif, Maryam and Rouhani, Saee},  
title = {Data Mining Approach based on Neural Network and Decision Tree Methods for the Early Diagnosis of Risk of Gestational Diabetes Mellitus}, 
abstract ={Introduction: Nowadays, in this industrial modern world, the incidence of chronic diseases has been significantly increased. Gestational diabetes mellitus is one of the major health problems that if not treated, it will cause serious complications for mother and her child. The purpose of this research was to find ways for determining the risk of gestational diabetes mellitus and making early diagnosis to prevent it in the initial stages of pregnancy. Methods: This applied-survey research used two approaches of neural network and decision tree in experimental analysis of data and prediction. The extracted data were normalized and analyzed through Matlab software. Results: The results showed that data-based method is effective in improving the accuracy of prediction and has good performance in discovering implied knowledge and diagnosis of hidden relationships among data. In both methods, decision errors were acceptable and very close to each other. Conclusion: Based on the obtained results, data mining methods can be used in health centers for less familiar diseases in order to achieve on-time diagnosis, patient management and to decrease treatment costs.  },  
Keywords = {Data mining, Artificial Neural Network, Decision Tree, Gestational diabetes mellitus, Diagnosis},
volume = {4},
Number = {1}, 
pages = {59-68}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-181-en.html},  
eprint = {http://jhbmi.ir/article-1-181-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {AshrafiRizi, Hass},  
title = {challenges of  Medical Universities\' Journals}, 
abstract ={},  
Keywords = {},
volume = {4},
Number = {1}, 
pages = {69-70}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-183-en.html},  
eprint = {http://jhbmi.ir/article-1-183-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Varzeshnejad, Maryam and Namnabati, Mahboobeh and Taleghani, Faribai},  
title = {A Successful Step towards Application of Informatics in Nursing in Iran}, 
abstract ={Introduction: Nowadays, due to the increasing development of nursing science and demand for improving and enhancing the quality of nursing care, the necessity of integrating informatics with Nursing Science for proper management of nursing information flaunts more than ever. Therefore, the present study aimed to develop the electronic information system of nursing as a step towards the integration of informatics science with nursing science. Methods: The present study was conducted using technical action research approach. The main stages of the study were the development of a nursing electronic information system, its implementation, application and evaluation in a neonatal intensive care unit in 2016. Descriptive statistics was used for the analysis of quantitative data and qualitative data obtained from interviews were analysed using content analysis and coding. Results: The results of Satisfaction Scale Questionnaire showed satisfaction of nurses with the components and applications of the electronic system. Nurses' information about drugs and the process of nursing increased after using the system. Content analysis of qualitative findings also led to exploit the main categories of enhancing the quality of care, improving the documentation process, professional development, continuing education and learning, the integration of theory and practice in the application of the nursing process, human and equipment barriers. Conclusion: According to the obtained results, paying attention to the design of a native system based on the needs of nurses and the participation of the beneficiaries could take a small but successful step toward effective use of informatics science in nursing.  },  
Keywords = {Electronic Nursing Information System, Action Research, Neonatal Intensive Care, Nursing, Informatic},
volume = {4},
Number = {2}, 
pages = {71-83}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-186-en.html},  
eprint = {http://jhbmi.ir/article-1-186-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Eghbali-Zarch, Maryam and TavakkoliMoghaddam, Reza and Sepehri, Mohammad Mehdi and Esfahanian, Fatemeh and Azaron, Amir},  
title = {Optimizing and Cost-effective Analysis of Medication Treatment of Type 2 Diabetes for Prevention of Hypoglycemia Using Markov Decision Process}, 
abstract ={Introduction: Type 2 diabetes (T2D) imposes high expenses on societies, due to its effects on individual and social functions of patients. Adverse complications of this disease can be prevented through controlling patient's blood sugar level. The purpose of this study was to optimize the medication treatment of type 2 diabetes. Methods: In this applied survey, Markov decision process (MDP) was used to model the scheduling and sequencing of T2D medication treatments. In order to have a model close to reality, expense issues, time value of money (TVM) and inflation were considered and it was tried to plan a cost-effective treatment program. Since anti-diabetic drugs cause hypoglycemia in elderly patients, a hypoglycemia preventive approach was applied on the proposed model and its effect was analyzed. The function of proposed model and efficiency of the obtained optimal policy were compared with clinical guidelines. Moreover, in order to address the model behavior, sensitivity analysis on parameters related to treatment costs was also conducted. Results: The proposed model showed better performance in glycemic control compared to clinical guidelines. Treatment cost parameters affected treatment program. Conclusion: In general, optimizing the medication treatment of T2D not only can improve patients' life period with quality, but also can decline high costs imposed on societies’ healthcare systems.    },  
Keywords = {Medical decision making, Type 2 Diabetes, Hypoglycemia, Optimization, Markov decision process},
volume = {4},
Number = {2}, 
pages = {84-97}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-207-en.html},  
eprint = {http://jhbmi.ir/article-1-207-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Nazeri, Najme and Dorri, Sara and Atashi, Alirez},  
title = {The Effective Factors on Success of E-learning in Medical Sciences Fields}, 
abstract ={Introduction: Today, the use of information technology in education, is one of the most important goals of many educational institutions around the world and Iran, due to its advantages including the possibility to be used at any time and place. ACECR  branch of Tehran University of Medical Sciences, as one of the organizers of specialized training courses, has already organized some e-learning courses. In this research, we tried to examine the role of each of the effective factors in e-learning in the success rate of this type of education. Methods: In this descriptive study, the effect of six factors, from the perspective of the four groups of participants, professors and ACECR (Iranian academic center for education, culture and research) staff and managers, was measured in 2010-2011, through using a researcher-made questionnaire including 39 questions on Likert scale. The questionnaire was sent via e-mail to 420 people and a total of 188 people participated in this study. The collected data were analyzed through SPSS software and using descriptive statistics and inferential statistics.  Results: The results indicated the importance of all studied factors with the order of management, educational content, facilities, teachers, rules and learner. Conclusion: Although the difference between the effective factors is negligible, the extra effort of authorities to remove the shortcomings and weaknesses of the three main and effective factors of management, educational content and facilities needed for the success of e-earning is required},  
Keywords = {E-learning, E-Training, Success Factors },
volume = {4},
Number = {2}, 
pages = {98-107}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-218-en.html},  
eprint = {http://jhbmi.ir/article-1-218-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {EsmaeeliGohari, Reza and EsmaeeliGohari, Elham and Shafiei, Mehdi},  
title = {Detection of Crimean-Congo Fever Using C4.5 Decision Tree}, 
abstract ={Introduction: The prevalence of Crimean-Congo fever, a common disease between human and animal, shows an increasing rate by coming summer season. Detection of this disease by the use of necessary tests, lasts at least about one week. There are several data mining and machine learning techniques to create predictive models for identifying at risk people. In this study, C4.5 decision tree method has been used due to its simplicity and efficiency. Methods: In this applied descriptive study, data related to suspected cases of Crimean-Congo fever were used. These data have been collected from health centers of Iran in a four-year period since 2014 and contained 965 records with 29 features. First, by using the quadratic programming feature selection method, the variables which were effective on the model were selected and then, the C4.5 decision tree model was created through using input variables and determining the target variable. Data analysis was performed through Matlab software. Results: According to the applied model, it was found that fever, bleeding, sudden onset of symptoms, increased liver enzyms, increased total Bilirubin, decreased Hemoglobin, Hematuria, Leukocytosis, Proteinuria and Leukopenia have the greatest impact in the diagnosis of this disease. Conclusion: According to the obtained results, the sensitivity of the proposed model is 95% and its specificity is 50%. Therefore, this model showed acceptable efficiency in diagnosing this disease in comparison with other studies done in medical data mining field.  },  
Keywords = {Medical decision support system, Disease diagnosis, Crimean-Congo hemorrhagic fever, C4.5 Decision tree},
volume = {4},
Number = {2}, 
pages = {108-121}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-225-en.html},  
eprint = {http://jhbmi.ir/article-1-225-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Mohammadi, Reza and Lazem, Mina and Ghalane, Sara and Aslani, Nasim and Garavand, Ali},  
title = {The Performance of Health Information Management Department in Valiassr Hospital}, 
abstract ={Introduction: With regard to the importance of Health Information Management in improvement of health care services, this study was done to determine the performance of Health Information Management Department of Valiasr hospital  of Tehran city in 2017. Methods: This mix-method study was done in 2017. For data collection in quantitative study, a valid and reliable check list and in qualitative study, 8 interviews were used. Excel 2013 and MAXQDA were used for the analysis of quantitative and qualitative data respectively. Results: According to the results, medical coding ward had poorer performance than other wards (2.37 out of 3). The problems of Health Information Management Department of Valiassr hospital were categorized in five main categories including organizational, human resources, financial, infrastructural and hardware and knowledge and professional categories. Also, scan of main sheets was the most important performed activity. Conclusion: With regard to the results of the present study, it is suggested that policy makers pay special attention to Health Information Management.  },  
Keywords = {Performance, Health information management, Medical records},
volume = {4},
Number = {2}, 
pages = {122-131}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-209-en.html},  
eprint = {http://jhbmi.ir/article-1-209-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Babaei, Melika and Karim, Hesam and RostamNiakan, Sharareh},  
title = {Designing a Drug Delivery System for Regulation of Blood Pressure Using Fuzzy Controller}, 
abstract ={Introduction: According to the importance of hypertension, the control and stabilization of blood pressure level is very important. The purpose of this study was to design a system for controlling and regulating arterial blood pressure by using sodium nitroprusside through a fuzzy controller. Methods: This is an applied study done through cross-sectional method. At first, related studies in the field of designing mathematical models for regulation of blood pressure were investigated. Then, by surveying the results of these studies, the best model was selected and necessary changes were made. In the final phase, the fuzzy controller was designed for blood pressure regulation. All processes of designing and implementation of Fuzzy system were performed in 2010 version of MatLab software. Results: In the first phase, the fuzzy controller caused rapid and sudden changes in output. Therefore, by modifying the controller to improve the system, the system was able to control the blood pressure after about 3 minutes and returned it to the normal level. But, again, the output of the controller had quick changes. So, by applying a filtered controller, high frequencies were controlled and blood pressure remained constant within about 1 minute. Conclusion: By using fuzzy control and valid mathematical models,   blood pressure can be controlled and stabilized. Classical methods in dealing with biological systems are highly dependent on model parameters. But, fuzzy control, in facing uncertainty, provides an acceptable response with an acceptable speed.  },  
Keywords = {Blood pressure, Fuzzy controller, Sodium Nitroproside, Medical Informatics},
volume = {4},
Number = {2}, 
pages = {132-141}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-206-en.html},  
eprint = {http://jhbmi.ir/article-1-206-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Nekoei, Mansoureh and Nezamabadi-pour, Hossein and Rashedi, Esmat},  
title = {Classification of L/R Hand Motor Imagery in Brain Computer Interfaces Using Feature Selection by Metaheuristic Algorithms}, 
abstract ={Introduction: Pattern recognition field is necessary for the recognition of different sensorimotor tasks in Brain Computer Interface systems. Reducing the number of features is an important step in Brain Computer Interface systems and it can improve the accuracy and efficiency of the classification and reduce the costs. Methods: In this paper, features selection was performed through using Improved Binary Gravitational search algorithm and Advanced Binary Ant Colony Optimization on data related to brain signals of nine normal subjects for imagination of left and right hand movements.  Features were extracted from six different frequency bands. Two classifiers including support vector machine and k- nearest neighbor were applied to separate the classes. Data were processed by EEGLAB toolbox and through matlab software. Results: The classification rate of the proposed method is 84.21%. Using feature selection methods, effective frequency bands and features for left and right hand movement classification were extracted. Conclusion: The results show the improvement in the classification rate by using Improved Binary Gravitational search algorithm and nearest neighbor classification.  },  
Keywords = {Algorithm, Advanced Binary Optimization, Support Vector Machine},
volume = {4},
Number = {2}, 
pages = {142-153}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-188-en.html},  
eprint = {http://jhbmi.ir/article-1-188-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Langarizadeh, Mostafa and Orooji, Azam},  
title = {De-identification of Electronic Health Records Using Machine Learning Algorithms}, 
abstract ={Introduction: Electronic Health Record (EHR) contains valuable clinical information that can be useful for activities such as public health surveillance, quality improvement, and research. However, EHRs often contain identifiable health information that their presence limits the use of the records for sharing and secondary usages. De-identification is one of the common methods for protecting the confidentiality of patient information. This systematic review has focused on recently published studies on the usage of de-identification methods based on Machine Learning (ML) approaches for removing all identifiable information from electronic health records. Methods: A systematic review was performed in electronic databases like PubMed and ScienceDirect between 2006 and 2016. Studies were assessed for adherence to the CASP checklists and reviewed independently by two investigators. Finally, 12 articles were matched with inclusion criteria. Results: The selected studies have been discussed in terms of used methods and knowledge resources, types of identifiers detected, types of clinical documents, challenges and achieved results. The results showed that ML-based de-identification is a widely invoked approach to protect patient privacy when disclosing clinical data for secondary purposes, such as research. Also, the combination of the ML algorithms and some techniques such as pattern matching and regular expression matching could decrease need to train data. Conclusion: There is a lot of identifiable information in medical records. This study showed ML- based de-identification methods can intensively reduce the disclosure risk of information.  },  
Keywords = {Confidentiality, Privacy, De-identification, Machine Learning},
volume = {4},
Number = {2}, 
pages = {154-167}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-211-en.html},  
eprint = {http://jhbmi.ir/article-1-211-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Tanhapour, Mozhgan and Safaei, Ali Asghar},  
title = {Designing and Modeling Personal Health Record Systems based on Health Social Network}, 
abstract ={Introduction: Patient-centered care is one of the six major aims to achieve high quality healthcare.  Personal health records can improve patient-centered cares. Also, there is growing desire to use internet and its services in healthcare. The purpose of this study was to design the architecture of personal health record system in the health social network platform. Methods: In this descriptive study, designing the architecture of the proposed system was done by Unified Modeling Language (UML). First, system components and their relationships were modeled by class diagram. Then, the use-case diagram showed how the proposed system interacts with its environment. Ultimately, the activities in the main process of the proposed system were modeled by the activity diagram.Finally, the designed architecture was evaluated by scenario-based assessment (ARID) method. Results: The scenario-based assessment (ARID) showed that the designed architecture by UML and determined relationships between components, systems and users from the structural and behavioral perspective could meet all expected scenarios from the proposed system. Conclusion: The modeling of the proposed system showed that a social network can meet the features of personal health record and the expectations of its users. The use of web 2.0 and its services lead to better and faster information exchange and dissemination, training, emotional support and etc.  },  
Keywords = {Patient-centered care, Personal health record, web 2.0, Social network, Unified Modeling Language},
volume = {4},
Number = {3}, 
pages = {168-180}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-191-en.html},  
eprint = {http://jhbmi.ir/article-1-191-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {SalehiNejad, Simin and Azami, Mohammad and Motamedi, Fatemeh and Bahaadinbeigy, Kambiz and Sedighi, Behnaz and Shahesmaili, Armit},  
title = {The Effect of a Web-based Information Intervention on Caregiving Burden in Caregivers of Patients with Dementia}, 
abstract ={Introduction: Due to the relatively high rate of psychological problems among Dementia caregivers, they need necessary information about this disease and methods of care giving. This study aimed to improve caregivers’ awareness on this disease in order to improve their performance and the quality of patient care and to reduce their stress through the provision of web-based health information. Methods: This clinical trial used intervention and control groups. The sample size was calculated as 25 in each group (total=50). First, subjects were selected through purposive sampling and were randomly divided into the test and control groups. Then, a pre-test was carried out using knowledge and care scale questionnaires. In the next step, through a site designed for this purpose, health information related to the disease was provided to careers in 12 sessions within two months. After the end of the intervention, post-test was performed in both groups and the results were analyzed using descriptive and inferential statistics. Results: According to the obtained results, mean score of caregiving burden showed no significant change in the control group and it, even, showed a little increase (0.53), while, in the test group, it decreased by 13.58 points. Conclusion: It can be concluded that the provision of web-based health information is effective in reducing caregiving burden of Dementia caregivers.    },  
Keywords = {Health information, Web, Caregiver burden, Dementia},
volume = {4},
Number = {3}, 
pages = {181-191}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-236-en.html},  
eprint = {http://jhbmi.ir/article-1-236-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Kohzadi, Zahra and Kohzadi, Zeinab and Afrash, Mohammadreza and Shahmoradi, Leil},  
title = {Designing a Fuzzy Logic Intelligence System for Driver\'s Health Assessment}, 
abstract ={Introduction: If driver’s health is not controlled in the community, it might cause the death of healthy people in the best period of their lives in terms of performance, efficiency and health and it imposes a lot of financial cost on the country. The aim of this study was to Design an intelligent systems based on Fuzzy logic to determine the drivers' health condition.   Methods: In this retrospective study, 350 health records of drivers referred to Ilam Occupational Medical Center were selected. Then, clinical information was collected from driver’s health record as a checklist and considering the criteria of accuracy, sensitivity and specificity and the area under the ROC curve, the proposed model was analyzed. Moreover, Kappa test was used for evaluation of the rate of adjustment of system results with the recorded diagnosis in the medical file. Matlab2013 was used for designing the operative rabbet.   Results: The specificity, sensitivity and accuracy of the introduced fuzzy model were respectively 87%, 99.3% and 96.9% and kappa rate of 87% showed relatively complete adjustment of the reported rate and the area under Roc curve was calculated as 92.02. Conclusion: According to the findings of this study, the presented fuzzy system for determining the drivers' health condition can play an important role in helping physicians and can be used in occupational medicine centers for increasing the speed and accuracy and reducing costs.    },  
Keywords = {Drivers' health measurement, Fuzzy Intelligent Systems, Fuzzy Logic},
volume = {4},
Number = {3}, 
pages = {192-200}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-201-en.html},  
eprint = {http://jhbmi.ir/article-1-201-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {EsmaeeliGohari, Elham and Zarifzadeh, Sajjad and Hasanvand, Saee},  
title = {A Hybrid Method for Query Recommendation in Recommender Systems}, 
abstract ={Introduction: The rapid growth of information in the Internet and high informational overload has created an important challenge for users in accessing their needed information. Nowadays, query recommendation systems have become a major part of information retrieval systems. One of the applications of these recommendation systems is in medical sciences. Through applying personalization approach, these systems attempt to decrease the problem of informational overload in Web and to accelerate users' medical search. Method: In this applied and descriptive study, by using the lexical features and search results of queries, we tried to propose a method that helps users to access their desired information in a short time while maintaining the lexical relationship with the original query. The popular k-means algorithm was used to cluster queries. The implementation of the proposed method was done by using java programming language and in NetBeans IDE software. Results: According to the proposed method, the combined use of the lexical features and search results of queries leads to useful information for detecting similar queries. Since there is a possibility that a query contains multi-meaning words, using search results can be useful in identifying the user’s intent of a query. Conclusion: Evaluation of the proposed model with the real search log of the Parsijoo search engine indicated the precision rate of 77.4% for this method that in comparison to other methods shows 10% improvement of precision.  },  
Keywords = {Medical recommendation system, query recommendation, Search engine, Information retrieval},
volume = {4},
Number = {3}, 
pages = {201-215}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-234-en.html},  
eprint = {http://jhbmi.ir/article-1-234-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Karami, Sedighe and Asadi, Farkhondeh and Emami, Hass},  
title = {Thematic Categorization of Mobile Health Software Packages and their Priority from the Perspective of Iranian Physicians}, 
abstract ={Introduction: Mobile health is the use of mobile and wireless technologies for health-related goals. To this end, various mobile applications have been created in different medical fields. The goal of this study was subject categorization of mobile health applications in Iran and to find their priority according to physicians.  Methods: This was a descriptive study. The study population consisted of all Iran mobile applications and also specialized physicians from Iran University of Medical Sciences, Shahid Beheshti and Tehran universities of medical sciences. First, mobile health applications in Iran were investigated and categorized based on their subject area and then their priority from the perspectives of physicians was determined using a researcher-made questionnaire. Results: Based on the application and physicians views, mobile health applications were divided into 21 categories of prevention, diagnosis and treatment, general and plastic surgery, medical tests, medical calculations, radiology, nursing, psychology, self-care, medical education, anatomy and atlases, medical informatics, medicine and pharmacy, rehabilitation, glossary and abbreviations, journals, medical ethics and rights, consultation, emergency and relief, social harm and traditional medicine. Conclusion: It is necessary that developers of mobile health software consider the identified priorities in developing applications in order to make physicians and general users more willing to use mobile health services.  },  
Keywords = {Mobile health applications, Mobile health, Subject categorization},
volume = {4},
Number = {3}, 
pages = {216-221}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-233-en.html},  
eprint = {http://jhbmi.ir/article-1-233-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Jalalian, Faezeh and Jebali, Ali},  
title = {A Study on the Effect of Seven Different Compounds of Cannabis Extract on the Accumulation of Amyloid Peptide in Alzheimer\'s Disease through Molecular Simulations}, 
abstract ={Introduction: Alzheimer's disease is a progressive cerebrovascular disease with irreversible damage, which gradually degrades the mental abilities of the patient. In this study, amyloid peptide was exposed to seven different compounds in the canaboid extract and then, the structure and thermodynamic parameters were evaluated. Methods: In this study, the three-dimensional structure of beta-amyloid peptide in patients with Alzheimer's disease was prepared from the rcsb database. The main components of canaboid extract were obtained from CHEBI database too. Then, amyloid peptide was subjected to each of the canaboid extract molecules in the molecular dynamics simulation software, and its structural and thermodynamic characteristics were evaluated over 3000 picoseconds. Results: Comparison of seven different compounds of cannabis extract showed that all cannabis extract compounds were able to change the structure of amyloid peptide. Each compound was able to change the effective surface and volume, and the level of lipophilicty of amyloid peptides. Conclusion: The ability of these compounds to change the volume and surface is effective in preventing amyloid peptide accumulation. The findings of this study should be investigated in a laboratory scale and then on the human body to detect the efficacy of canaboid extract components exactly.  },  
Keywords = {Amyloid peptide, Alzheimer's disease, Cannabis extract, Simulation, Molecular dynamics},
volume = {4},
Number = {3}, 
pages = {222-231}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-253-en.html},  
eprint = {http://jhbmi.ir/article-1-253-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Piri, Zakie and DehghaniSufi, Mahsa and Salimzadeh, Zeynab and Ashragh, Bahareh and Alizadeh, Ghasem},  
title = {Heart Failure Management via Mobile Phones: A Systematic Review}, 
abstract ={Introduction: Advances in telecommunication technologies have created new opportunities to provide telemedical care as an adjunct to medical management of patients with heart failure. One of the proposed strategies for helping heart failure patients in managing their disease is using mobile phone which is now growing rapidly worldwide. However, the efficacy of this system is not well known. The objective of this systematic review was to determine the effects of mobile use on heart failure management. Methods: In this review, published studies from 2009 to January 2015 that were accessible in PubMed, ScienceDirect, Scopus and Proquest were searched and from 1021 related studies, 69 articles were identified by their titles and finally, after applying inclusion and exclusion criteria, 11 articles were selected for review. Results: In whole, 32 outcomes had been studied in the selected papers and the review showed that in 14 cases, the intervention had led to significant positive effect and in 11 cases, the intervention had non-significant positive effect. While, in 5 cases, the intervention had no effect and in 2 cases, it had led to a negative effect. Conclusion: According to the results of this review, using mobile phones could be beneficial in the management of Heart Failure and delivery of health services to the affected patients.  },  
Keywords = {Heart Failure, Systematic Review, Mobile phone, Telemedicine},
volume = {4},
Number = {3}, 
pages = {232-241}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-196-en.html},  
eprint = {http://jhbmi.ir/article-1-196-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Shahmoradi, Leila and Tabari, Parinaz},  
title = {Application of Cloud Computing in Health and its Review in Iran}, 
abstract ={},  
Keywords = {},
volume = {4},
Number = {3}, 
pages = {242-243}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-214-en.html},  
eprint = {http://jhbmi.ir/article-1-214-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2017}  
}

@article{ 
author = {Kabir, Mohammad Javad and AshrafianAmiri, Hasan and Rabiee, Seyed Mozafar and keshavarzi, Anahita and Hosseini, Sohila and NasrollahpourShirvani, Seiyed Davou},  
title = {Satisfaction of Urban Family Physicians and Health Care Providers in Fars and Mazandaran Provinces from Integrated Health System}, 
abstract ={Introduction: Electronic health record is electronic data of “entire life of a person” registered by healthcare providers and shared in different health centers. The electronic health record has been announced to all medical universities of the country since 2015 by launching the Integrated Health System (SIB). This study aimed to determine the satisfaction of urban family physicians and health care providers in Fars and Mazandaran provinces from SIB. Methods: This cross-sectional study was conducted in the winter of 2016 on urban family physicians and health care providers who were selected by systematic random sampling. Data collection tool was a researcher-made questionnaire consisting of 2 parts: demographic variables with 8 open and closed questions and satisfaction with 8 closed questions on Likert scale. The validity and reliability of the questionnaire were confirmed. Results: The total number of 464 participants included 236 (50.9%) physicians and 228 (49.1%) health care providers. From these, 273(58.8%) were employed in Fars province and 191(41.2%) in Mazandaran province. The majority of participants (65.5%) were women. mean score of satisfaction of SIB (from 5 points) in general was 2.94±0.8, and it was 2.89±0.8 in the Fars and 3.03±0.7 in the Mazandaran provinces. Mean score of satisfaction was 2.75±0.7 in urban family physicians and 3.04±0.8 in health care providers. Satisfaction level showed significant difference based on participants' type of occupation (P=0.0001) and province (P=0.122). Conclusion: The results showed that the satisfaction of employees was lower than the average level. It is recommended to redesign the structure of SIB more consistent with the needs of employees and with a user-oriented approach.  },  
Keywords = {Urban Family physician, Health electronic record, SIB, Health care providers},
volume = {4},
Number = {4}, 
pages = {244-252}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-252-en.html},  
eprint = {http://jhbmi.ir/article-1-252-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2018}  
}

@article{ 
author = {Taghavi, Asma and Monem, Hosei},  
title = {Increasing the Efficiency of Using CCU Beds of Hospitals through Optimization and Combination of Genetic Algorithm and Imperialist Competitive}, 
abstract ={Introduction: Hospitals as the most important consumer of resources in healthcare section are highly sensitive to maximum consumption of minimum existing resources. In the recent two decades, computer data processing to extract knowledge and improve utilization of resources has attracted the attention of organizations. In this study, allocation of CCU beds in Shahid Faghihi Hospital of Shiraz is investigated through optimizing and combining Genetic Algorithm (GA) and Imperialist Competitive Algorithm (ICA). Methods: In this analytic cross-sectional study, patients were monitored through optimization and combination of genetic algorithm and imperialist competitive and allocated to CCU beds in the spring of 2016. To this end, number of patients, number of beds, number of doctors and vital signs of patients were used as input and configuration of patients and allocation optimization were considered as output. MATLAB 2012 was used to analyze data. Results: Results of this study show that ICA is more efficient compared to GA in optimization of allocating CCU beds to patients. Moreover, the hybrid algorithm obtained from combination of ICA and GA is more efficient than ICA.     Conclusion: In the process of this study, priorities of patients' hospitalization and also manner of hospitalization were determined and suggestions for allocation of beds to patients were presented.  },  
Keywords = {Optimization, Resource allocation, Genetic Algorithms, Imperialist Competitive A algorithms, Hybrid Algorithm, CCU},
volume = {4},
Number = {4}, 
pages = {253-265}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-258-en.html},  
eprint = {http://jhbmi.ir/article-1-258-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2018}  
}

@article{ 
author = {Dehghan, Parvaneh and Mogharabi, Maedeh and Zabbah, Iman and Layeghi, Kamran and Maroosi, Ali},  
title = {Modeling Breast Cancer Using Data Mining Methods}, 
abstract ={Introduction: Breast cancer is the most common form of cancer in women. Breast cancer detection is considered as one of the most important issues in medical science. Diagnosis of benign or malignant type of cancer reduces costs and also is important in deciding about the treatment strategy. The aim of this study was to provide data mining based models that have the predictability of breast cancer detection. Methods: This study was descriptive-analytic. Its database included 683 independent records containing nine clinical variables in the UCI machine learning. Multilayer Perceptron artificial neural network, Bayesian Neural Network and LVQ neural network were used for classification of breast cancer to benign and malignant types. In this study, 80% of data were used for network training and 20% were used for testing. Results: After pre-processing the data, different neural networks with different architectures were used to detect breast cancer. In the best condition, we could predict benign or malignant cancer in the MLP neural networks, LVQ and Bayesian Neural Networks with an average of ten tests with an accuracy of 97.5% and 97.6% and 98.3% respectively. Our investigations showed that Bayesian neural network had a better performance. Conclusion: Breast cancer is one of the most common cancers among women. Early diagnosis of disease reduces healthcare costs and increases patient survival chance. In this study, using data mining techniques in diagnosis, the researchers were able to use Bayesian neural network to achieve high accuracy in diagnosis.  },  
Keywords = {Breast Cancer, Neural Networks, LVQ, Data Mining},
volume = {4},
Number = {4}, 
pages = {266-278}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-208-en.html},  
eprint = {http://jhbmi.ir/article-1-208-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2018}  
}

@article{ 
author = {Mehdizadeh, Hamed and Fadaizadeh, Li},  
title = {Re-designing and Evaluation of Tele-dermatology Software for Skin Diseases}, 
abstract ={Introduction: The continuous increase in the demand for specialized skin care services,  together with the unbalanced geographical distribution of these specialists, has limited the access of patients to these services. Teledermatology is one of the innovative approaches that can be considered as a solution to improve the access to specialized skin care services with minimal material resources in developing countries such as Iran. Methods: The present study is an applied and aimed to re-designing and evaluating tele-dermatology software. In this research, redesign of the software was done through obtaining the users feedback after being used in clinical setting, then final version of the software designed and usability evaluation test was conducted. Results:  The usability testing result, show dermatologist and GP were very satisfied with the system and overall average scores obtained were 8 out of a total of 9 achievable scores. The scores earned was respectively: 7.8  for overall reaction to the system, 8.5 for screen feature, 7.9 for terminology and system information, 8.3 for Learning and 7.5 for system capability. Conclusion: The experience gained from this research shows that for the successful development and use of telehealth tools, need engage and collaboration with main stakeholder, identify, understand and modeled work flows and processes related to the provision of patient services and treatment. Also in order to increase the usability and user satisfaction, the design and development of systems should be based on the principle of user-centered design and engagement of system stakeholders at all stages of system design and development.  },  
Keywords = {E-Health, Teledermatology, User-centered Design, Usability, Satisfaction},
volume = {4},
Number = {4}, 
pages = {279-290}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-275-en.html},  
eprint = {http://jhbmi.ir/article-1-275-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2018}  
}

@article{ 
author = {LalDahti, Javad and Mohammadi, Mohsen and PadidaranMoghadam, Farhang},  
title = {A Method for the Diagnosis of Metabolic Syndrome based on KNN Data Mining Algorithm: A case study in Shohada-ye Kargar Hospital in Yazd, Iran}, 
abstract ={Introduction: Metabolic syndrome is a group of risk factors for developing cardiovascular diseases and diabetes in an individual. The presence of various signs and symptoms makes the diagnosis of this disease difficult. Data mining can provide clinical data analysis of patients for medical decision-makings. The purpose of this study was to provide a model for increasing the predictive accuracy of metabolic syndrome. Method: In this applied-descriptive study, the medical records of 1499 patients with metabolic syndrome with 15 characteristics were investigated. Patients' information is collected from the standard database of Yazd Shohada-ye kargar Hospital. Each patient was followed for at least one year. In this paper, GBC algorithm was used to optimize the results of KNN data mining algorithm to predict and diagnose metabolic syndrome, and a new model was presented. Results: Based on the objective function to predict the increase of blood lipids in the proposed method, gray wolf algorithms, particle swarm and genetics were used to improve the performance of the KNN algorithm. The analyses show that the proposed model with the precision accuracy of 0.921 has a greater accuracy compared to  fuzzy methods, backup vector machine, tree decomposition and neural network. Conclusion: Search in medical databases for the purpose of obtaining knowledge and information to predict, diagnose, and decision making are some applications of data mining in medicine. Hereditary algorithms can be used to optimize data mining techniques. The prediction and proper diagnosis of metabolic syndrome by using artificial intelligence and machine learning increases the chance of successful treatment.  },  
Keywords = {Metabolic syndrome, Bee colony algorithm, Decision tree},
volume = {4},
Number = {4}, 
pages = {291-304}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-229-en.html},  
eprint = {http://jhbmi.ir/article-1-229-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2018}  
}

@article{ 
author = {Keikha, Masou},  
title = {Phylogenetic Analysis of Nocardia spp. using 16S rRNA, hsp65 and gyrB Genes}, 
abstract ={Introduction: Nocardia is one of the most important aerobic actinomycetes that lives in soil and can enter the human body by inhalation and traumatic inoculation and causes Nocardiosis. Molecular methods are one of the best methods for rapid and accurate identification and differentiation of species of this group of bacteria. The purpose of this study was evaluation of three housekeeping genes in identification and differentiation of most important species of Nocardia. Methods: In this study cross-sectional, first, gene sequences of 16S rRNA, gyrB and hsp65 for ten species of Nocardia were obtained from Genebank (NCBI). Then, those sequences were transferred to MEGA 5.0. Finally, phylogenetic trees based on each of 16S rRNA, gyrB and hsp65 genes were drawn. Results: Phylogenetic trees analysis based on 16S rRNA, gyrB and hsp65 gene sequences indicated that all of these genes could identify and differentiate Nocardia species. Also, it was found that gyrB gene is the best option for drawing the phylogenetic relationships of Nocardia species. Conclusion: According to this research, for accurate identification of Nocardia species, several housekeeping genes should be investigated simultaneously.  },  
Keywords = {Nocardia, Phylogenetic analysis, 16S rRNA},
volume = {4},
Number = {4}, 
pages = {305-312}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-189-en.html},  
eprint = {http://jhbmi.ir/article-1-189-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2018}  
}

@article{ 
author = {ErshadSarabi, Roqhayeh and Sadoughi, Farahnaz and JamshidiOrak, Rouhangiz and Bahaadinbeigy, Kambiz},  
title = {Role of Mobile Technology in Iran Healthcare System: A review study}, 
abstract ={Introduction: Mobile technology has provided new opportunities for health care systems. Improvement of health services outcomes in different patient groups is one of the benefits of using this tool. Although the use of mobile in Iran is expanding, there is no evidence of the state and the use of this technology in health system. The aim of this study was to review published researches on the application of mHealth in the health system of Iran. Methods: In order to carry out a review study, Pubmed database was searched by the keyword "mobile Health" and its equivalents which have derived from the "Medical Subject Headings". Iranian databases including Iran medex, Magiran and Scientific Information Database (SID) were also searched for Persian and English terms of mobile health. Retrieval citations from information databases were sent to the endnote software and evaluated based on the considered criteria. Results: The research sample consisted of 26 articles that met the criteria of the study. In most of studies, text messaging was the main intervention tool of mHealth. The results indicated significant effect of mobile health in improving the patients' care. Conclusion: In Iran, mobile health can be effectively used in the health system due to population structure and geographic extent. According to the results of this study, the use of mobile health, especially in educating patients for self-care and preventing the spread of diseases, can be very effective.  },  
Keywords = {Mobile health, Mobile Phone, Cell Phones, Text Messaging, Health care system},
volume = {4},
Number = {4}, 
pages = {313-326}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-226-en.html},  
eprint = {http://jhbmi.ir/article-1-226-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2018}  
}

@article{ 
author = {AlishanKarami, Nader and HajiZeinolabedini, Mohsen and Radad, Iraj and Ghazi-Mirsaeid, Seyed Jav},  
title = {Application and Role of Ontologies in Biomedical Information Retrieval Systems}, 
abstract ={Introduction: Ontologies improve the quality of information retrieval (IR). Therefore, it is important to better know the process of ontology engineering and their application in IR. The aim of this research was to identify the engineering methods of ontologies and also their application in biomedical IR. Method: This review was done through library research method with an analytical approach. Required information for the review was retrieved from Pubmed, Scopus and Web of Science using keywords: "Ontology-based biomedical Information Retrieval", "Information Retrieval", "Biomedical Information Retrieval",  "Ontology engineering", "Ontology construction",  "Biomedical Ontology" and "Ontology building" without time limit. Five articles addressing an ontology-based biomedical IR system were reviewed. Results: Studies on ontology based biomedical IR, started in 2004, are not limited to a single country. In general, ontologies are used to manage the semantic metadata. Although most IRs try to develop their own ontologies, reuse of earlier ontologies is a priority. The material for developing ontologies is taken from the literature in the domain. The studied ontologies have been produced by centralized approaches and decentralized approaches and different groups have not been used. Conclusion: The main purpose of systems for applying ontologies is using them to develop semantic metadata for helping machine reasoning.  },  
Keywords = {Information Storage and Retrieval, Biological Ontologies, Information Systems},
volume = {4},
Number = {4}, 
pages = {327-340}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-222-en.html},  
eprint = {http://jhbmi.ir/article-1-222-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2018}  
}