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:: Volume 4, Issue 1 (6-2017) ::
2017, 4(1): 39-47 Back to browse issues page
Determination of the Most Important Factors Affecting Non-Melanoma Skin Cancer Using Data Mining Algorithms
Foroughosadat Ghasemzadeh, Ali Arab-kheradmand, Soroush Daklan, Alireza Shabaninezhad, Ata Garajei, Kobra Etminani
Ph.D. in Software Engineering, Assistant Professor of Medical Informatics Dept., Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
Abstract:   (3670 Views)
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
Full-Text [PDF 1224 kb]   (1629 Downloads)    
Type of Study: Original Article | Subject: Special
Received: 2017/03/30 | Accepted: 2017/05/16
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Ghasemzadeh F, Arab-kheradmand A, Daklan S, Shabaninezhad A, Garajei A, Etminani K. Determination of the Most Important Factors Affecting Non-Melanoma Skin Cancer Using Data Mining Algorithms. Journal of Health and Biomedical Informatics. 2017; 4 (1) :39-47
URL: http://jhbmi.ir/article-1-204-en.html

Volume 4, Issue 1 (6-2017) Back to browse issues page
مجله انفورماتیک سلامت و زیست پزشکی Journal of Health and Biomedical Informatics
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