在AI时代,数学瘤学的未来
Russell C Rockne1, Morten Andersen2, Alexander R A Anderson3
1Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, CA, USA. rrockne@coh.org.
NPJ systems biology and applications
|January 26, 2026
概括
人工智能 (AI) 推进了机械建模和机器学习,以更快地发现瘤学中的更好的临床决策. 未来的人工智能将通过将机械主义的严谨性与数据驱动的洞察力相结合来增强数学瘤学.
科学领域:
- 数学瘤学数学瘤学
- 计算生物学 计算生物学
- 人工智能在医学中的应用
背景情况:
- 在机械建模和数据驱动机器学习的接口上出现的新进展.
- 人工智能加速发现,改进预测建模和增强临床决策的机会.
研究的目的:
- 讨论用于瘤学的人工智能的新兴进展.
- 解决当前AI方法的局限性.
- 在数学瘤学中提出人工智能的未来视角.
主要方法:
- 观点文章讨论了机械建模和机器学习的整合.
- 对当前人工智能局限性的分析.
- 对未来在瘤学中的人工智能应用的概念框架.
主要成果:
- 人工智能可以加速发现并改善瘤学中的预测建模.
- 人工智能有可能增强临床决策.
- 当前的人工智能方法有关键的局限性,需要解决.
结论:
- 提出了一个未来,人工智能可以增加机械严谨性,临床相关性和人类创造力.
- 建议重新定义数学瘤学的理解.
- 人工智能集成有望显著推进瘤学领域的发展.
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