基于人工智能的定位前列腺癌患者的个性化临床决策:手术与放射治疗相比
Yuwei Liu1, Litao Zhao2,3,4, Jiangang Liu2,3,5
1Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, People's Republic of China.
The oncologist
|July 31, 2024
概括
人工智能 (AI) 模型有助于个性化前列腺癌 (PCa) 治疗,通过识别那些从手术或放射治疗中获益更多的患者. 这种人工智能工具可以改善临床决策和患者的治疗结果.
科学领域:
- 在瘤学瘤学.
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
背景情况:
- 在手术和放射治疗之间,前列腺癌 (PCa) 治疗决策缺乏明确的个性化标准.
- 开发人工智能驱动的工具对于优化局部PCa的非保守治疗选择至关重要.
研究的目的:
- 开发和验证基于人工智能 (AI) 的模型,用于局部性前列腺癌 (PCa) 的个性化治疗建议.
- 确定哪些患者会从放射治疗或手术中获益更多,帮助临床决策.
主要方法:
- 来自监测,流行病学和最终结果数据库的大型数据集 (118,236名患者) 的分析.
- 开发人工智能模型来预测放射治疗生存概率 (RSP) 和手术生存概率 (SSP).
- 使用培训,内部和外部数据集验证最终治疗建议模型 (FTR).
主要成果:
- 人工智能模型在预测放射治疗和手术的生存概率方面表现出高准确性 (C指数:0.735-0.797).
- 与接受非推治疗的患者相比,接受AI推治疗的患者的存活率显著更高 (P < .001).
结论:
- 开发的AI模型 (FTR) 准确地确定了局部前列腺癌患者的最佳治疗途径 (放射治疗与手术).
- 这种人工智能工具为临床医生提供了一种有效的手段,可以增强个性化治疗选择并改善患者的治疗结果.
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