Mardani S, Rahman A, Nafissi N. An Agent- based Modeling for Breast Tissue Simulation and the Growth and Spread of Tumor in Various Breast Cancer States. jhbmi 2020; 6 (4) :272-287
URL:
http://jhbmi.ir/article-1-410-en.html
Ph.D. in Computer Engineering, Assistant Professor, Computer Engineering Dept., Faculty of Engineering, Roudehen Branch, Islamic Azad University, Roudehen, Iran
Abstract: (4486 Views)
Introduction: Breast cancer is a cancer that is caused by abnormal growth of breast cells. Modeling and simulation of the growth and treatment of breast cancer, along with providing the possibility of doing experiments and research, can reduce the time and cost of treatment by predicting some cases. The purpose of the present research was to develop an agent-based model for the simulation of breast tissue and the growth and spread of tumor in various breast cancer states.
Method: In this research, agent-based modeling and simulation method, as well as library studies were used. NetLogo software was used for designing and modeling of breast anatomy and development of model with the required knowledge. Then, according to the patient's age, tumor grading and cancer cells spread, simulation of the growth and development of various breast cancer states in different times were investigated. In order to validate the model, clinical data and reports related to the age and grade, size, growth and spread of tumor in a number of patients with breast cancer were studied and considered and compared with model outcomes.
Results: According to the experiments related to the analysis and validation of the model, the developed model had relatively acceptable results about the growth of breast tumors and the proliferation of cancerous cells in lymph nodes in various breast cancer states.
Conclusion: Agent-based modeling can be used as a relatively useful and efficient method in identifying and analyzing breast cancer behavior and predicting the growth and proliferation of cancer cells.
Type of Study:
Original Article |
Subject:
Artificial Intelligence in Healthcare Received: 2019/06/30 | Accepted: 2019/08/25