Volume 8, Issue 1 (6-2021)
jhbmi 2021, 8(1): 42-54 |
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Ph.D. in Computer Engineering, Assistant Professor, Computer Engineering Dept., Faculty of Engineering, Roudehen Branch, Islamic Azad University, Roudehen, Iran
Abstract: (2052 Views)
Introduction: Ovarian cancer is caused by malignant changes in the cells of the ovary. In various studies, cancer has been regarded as a biological system that has a set of characteristics; therefore, presenting a model of this system can considerably help to study and predict the phenomena related to the growth and spread of cancer. This study attempted to model and simulate the growth and spread of tumor in different stages of ovarian cancer and investigate the process of metastasis of ovarian cancer to other tissues and organs.
Method: In this research, modeling and simulation as well as library studies were used. First, it was attempted to design and model the anatomy of the ovary, fallopian tubes, uterus, lymph nodes of the ovaries, liver, and spleen. Then, different stages of ovarian cancer were modeled and simulated according to TNM system. NetLogo software was used for modeling and simulation.
Results: This study developed a model to simulate, visualize, and predict tumor growth and spread in different stages of ovarian cancer according to the TNM system as well as the ovarian cancer metastasis process.
Conclusion: By providing the possibility of further study and testing, development and utilization of models of ovarian cancer in its different stages can lead to better prediction of tumor growth sequence and behavior and selection of a better treatment option
Method: In this research, modeling and simulation as well as library studies were used. First, it was attempted to design and model the anatomy of the ovary, fallopian tubes, uterus, lymph nodes of the ovaries, liver, and spleen. Then, different stages of ovarian cancer were modeled and simulated according to TNM system. NetLogo software was used for modeling and simulation.
Results: This study developed a model to simulate, visualize, and predict tumor growth and spread in different stages of ovarian cancer according to the TNM system as well as the ovarian cancer metastasis process.
Conclusion: By providing the possibility of further study and testing, development and utilization of models of ovarian cancer in its different stages can lead to better prediction of tumor growth sequence and behavior and selection of a better treatment option
Type of Study: Original Article |
Subject:
Artificial Intelligence in Healthcare
Received: 2021/01/11 | Accepted: 2021/04/21
Received: 2021/01/11 | Accepted: 2021/04/21
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