将人工智能和机器学习集成到癌症临床试验中
John Kang1, Amit K Chowdhry2, Stephanie L Pugh3
1Department of Radiation Oncology, University of Washington, Seattle, WA..
Seminars in radiation oncology
|September 8, 2023
概括
人工智能 (AI) 正在通过改善临床试验中患者结果的预测来改变瘤学. 这篇评论探讨了最近的人工智能进步和数据驱动癌症护理的未来方向.
科学领域:
- 在瘤学瘤学.
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 瘤学实践涉及基于广泛的患者数据的复杂决策.
- 机器学习 (ML) 和人工智能 (AI) 为增强癌症护理数据分析提供了巨大的潜力.
- 在过去的五年里,人工智能从一个有前途的概念迅速发展到未来临床试验中的应用.
研究的目的:
- 审查人工智能在瘤学临床试验中的近期应用.
- 与传统的统计模型相比,讨论AI模型的解释.
- 探索人工智能的未来机会,特别是无监督和生成模型,在瘤学中.
主要方法:
- 关于人工智能在瘤学临床试验中的应用最新文献的综述.
- 分析AI在预测可操作结果中的作用.
- 讨论在临床实践中对AI模型的概念化和解释.
主要成果:
- 人工智能模型已经在预测急性护理访问,短期死亡率和外节延伸等结果方面取得了成功.
- 最近在临床试验中人工智能的努力表明,人们正朝着更好的预测可操作结果的方向迈进.
- 人工智能模型提出了不同的问题,需要不同的解释框架,而不是传统的统计方法.
结论:
- 人工智能在瘤学中变得越来越重要,提高了对患者结果的预测能力.
- 了解如何解释AI模型对于其有效的临床实施至关重要.
- 未来的瘤学人工智能应该利用无监督和生成模型来获得数据驱动的洞察力,而不是预定义的功能.
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