基于代理的方法用于瘤学中的生物建模:文献综述
Simon Stephan1, Stéphane Galland2, Ouassila Labbani Narsis3
1UTBM, CIAD UMR 7533, Belfort, F-90010, France; Université de Bourgogne, CIAD UMR 7533, Dijon, F-21000, France.
Artificial intelligence in medicine
|May 4, 2024
概括
计算建模,特别是瘤学中的基于代理物的建模 (ABM),正在推动生物学理解. 关键的挑战包括数据集成,模型验证和复杂生物系统的计算效率.
科学领域:
- 计算生物学是一种计算生物学.
- 系统生物学 系统生物学
- 生物信息学是一种生物信息学.
背景情况:
- 计算建模使用模拟来研究现实世界的现象,特别是生物相互作用.
- 它提供了一种有前途的方法来理解复杂的生物过程,并预测系统行为.
研究的目的:
- 审查最近关于生物系统计算建模的文献.
- 专注于使用人工智能 (AI) 和基于代理的建模 (ABM) 的瘤学应用从2010-2023.
主要方法:
- 在瘤学计算建模的文献综述.
- 分析使用人工智能 (AI) 和基于代理的建模 (ABM) 的研究.
主要成果:
- 大多数审查文章的重点是改善诊断和理解生物实体行为.
- 超启发式算法是最常用的模型.
- 确定的挑战包括知识结构,整体多尺度建模,新兴行为复制,验证,计算性能和数据隐私.
结论:
- 计算建模,特别是瘤学中的ABM,显示了促进生物理解的巨大潜力.
- 解决数据,验证和计算效率方面的挑战对于未来的发展至关重要.
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