生成性AI - 辅助自适应性癌症治疗
1Ted Rogers School of Information Technology Management, Toronto Metropolitan University, Toronto, ON, Canada.
Cancer control : journal of the Moffitt Cancer Center
|June 18, 2025
概括
适应性组合疗法使用动态调来对抗癌症耐药性. 本综述探讨了使用生成性AI (GenAI) 进行更准确的治疗预测和适应性癌症治疗建议.
科学领域:
- 在瘤学瘤学.
- 控制理论 控制理论
- 人工智能的人工智能
背景情况:
- 适应性组合疗法旨在通过动态调整基于癌症演变的治疗方法来克服癌症耐药性.
- 目前的模型需要提高准确性,可靠性和临床可行性,特别是新疗法和多式联络数据.
研究的目的:
- 审查生成AI (GenAI) 在增强自适应性癌症治疗方面的潜力.
- 探索GenAI如何预测治疗反应,并在非线性控制框架内推治疗.
主要方法:
- 非线性系统识别,控制理论和深度学习的整合.
- 在适应性癌症控制框架内应用这些方法,以利用不断扩展的癌症数据.
- 利用GenAI进行学习和推断能力.
主要成果:
- 提出了一种基因AI增强的适应性癌症治疗框架.
- 分析提供了对研究的概念清晰度和在瘤学中用于GenAI的翻译途径.
- 确定关键挑战,包括临床数据访问,深度学习可解释性和验证.
结论:
- 通过提高治疗反应预测和推,GenAI提供了一种有希望的方法来改善自适应性癌症治疗.
- 解决数据访问,模型透明度和临床验证方面的挑战对于将GenAI整合到瘤学中至关重要.
- 需要进一步的研究,才能在临床实践中实现GenAI辅助癌症治疗的全部潜力.
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