A stochastic Cellular Automata model of tumor-immune interaction
Publish place: کنفرانس بین المللی مهندسی برق
Publish Year: 1395
نوع سند: مقاله کنفرانسی
زبان: English
View: 722
This Paper With 10 Page And PDF and WORD Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
ICELE01_245
تاریخ نمایه سازی: 21 شهریور 1395
Abstract:
Cancer is a leading cause of death in the world. Mathematical and computer models may improve current treatments by helping scientists better understand of this disease. They may also introduce new aspects of therapy by predicting the result of changing microenvironment of the tumor or the interaction between different types of cells. In this paper, a square lattice Cellular Automata model of tumor-immune cell interaction is presented. The state of each tumor cell can be updated according to stochastic rules related to its previous state and the states of its Moore neighborhood. The growth fraction and necrotic fraction are used as output parameters beside a 2-D graphical growth presentation. The results show that entering immune system not only improves the compatibility of the model with physiological reality which show the impact of immune cells on tumor invasion, but also the results of output parameters are fitter to experimental data
Keywords:
Authors
Fateme Pourhasanzade
PhD candidate, Bioelectric Department, Research laboratory of Biomedical signals and sensors, Iran University of Sciences and Technology (I.U.S.T), Tehran, Iran
S. H Sabzpoushan
Assistant Professor, Bioelectric Department, Biomedical Engineering Faculty, Iran University of Sciences and Technology (I.U.S.T), Tehran, Iran
Ali Mohammad Alizadeh
Associate Professor, Cancer Research Center, Tehran University of Medical Sciences, Tehran, Iran
E Esmati
Professor, Department of Radiation Oncology, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :