在人工智能时代导航晚期细胞癌
Elie J Najem1, Mohd Javed S Shaikh2,3, Atul B Shinagare2,3
1Department of Imaging, Dana-Farber Cancer Institute, Boston, MA, USA. elie_najem@dfci.harvard.edu.
概括
人工智能 (AI) 在通过改善分期和治疗预测来管理晚期细胞癌方面表现有前途. 结合临床病理学和放射学数据的进一步研究可以增强AI.
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:
- 细胞癌 (RCC) 管理得到了改进,人工智能成为癌症研究的关键工具,特别是在瘤成像中.
- 虽然人工智能在RCC研究中表现有前途,但研究往往侧重于局部疾病,对晚期或转移性RCC的关注较少.
研究的目的:
- 总结一下人工智能在高级细胞癌 (RCC) 的进展.
- 突出AI在先进RCC的分期,风险分层和治疗反应预测方面的潜在临床价值.
- 解决AI模型开发的局限性,并建议未来的研究方向.
主要方法:
- 在细胞癌研究当前的人工智能应用的审查.
- 专注于AI在晚期和转移性疾病中的临床实用性.
- 对RCC中的AI的局限性和未来研究途径的分析.
主要成果:
- 人工智能在初始分期和识别高级RCC中高风险特征方面展示了潜力.
- 人工智能模型可以帮助预测晚期细胞癌的治疗反应.
- 当前人工智能模型的局限性需要进一步开发和验证.
结论:
- 支持人工智能的模型具有很大的潜力,可以促进先进的RCC的诊断和管理.
- 整合临床病理学和放射学数据可以在先进的RCC中优化AI模型性能.
- 未来的研究应该专注于强大的AI模型开发,以改善临床实践.
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