在非小细胞肺癌中人工智能预测:系统性审查
Michael Augustin1, Kelsey Lyons2, Hayeon Kim3
1Jacobs School of Medicine and Biomedical Sciences, University of Buffalo, Buffalo, NY.
American journal of clinical oncology
|July 18, 2025
概括
与传统方法相比,人工智能 (AI) 对非小细胞肺癌 (NSCLC) 的预后表现优越. 深度学习 (DL) 算法优于机器学习 (ML),为个性化癌症治疗提供了潜力.
科学领域:
- 在瘤学瘤学.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 非小细胞肺癌 (NSCLC) 的预后依赖于传统方法,如TNM分期.
- 人工智能 (AI) 提供了提高NSCLC预后准确性的潜力.
- 系统性审查对于评估AI在癌症预后中的作用至关重要.
研究的目的:
- 系统地审查AI算法在NSCLC预后中的应用.
- 为了比较不同AI类型 (ML与DL) 的预后性能.
- 综合人工智能输入数据和治疗干预的发现.
主要方法:
- 系统的文献审查遵循PRISMA指南.
- 基于输入数据 (组织学,CT,PET,MRI),治疗和预后表现的研究评估.
- 人工智能方法与传统系统 (如TNM分期) 的比较.
主要成果:
- 基于人工智能的预测始终优于传统方法,例如NSCLC的TNM分期.
- 深度学习 (DL) 与机器学习 (ML) 相比,显示出更高的预后性能.
- 人工智能利用各种数据,包括组织学,遗传学和成像 (CT,PET,MRI).
结论:
- 人工智能,特别是DL,显示了提高NSCLC预后的重大前景.
- 人工智能可以作为个性化的精确癌症治疗决策的宝贵补充工具.
- 在临床广泛采用之前,通过严格的临床试验进行进一步验证至关重要.
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