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人工智能在癌症患者营养不良的管理:一个系统的审查
Marco Sguanci1, Sara Morales Palomares2, Giovanni Cangelosi3
1A.O. Polyclinic San Martino Hospital, Genova, Italy.
Advances in nutrition (Bethesda, Md.)
|May 7, 2025
概括
人工智能 (AI) 在改善癌症患者的营养不良检测和管理方面显示出显著的希望. 人工智能模型准确地预测营养状况并优化干预措施,提高患者的治疗结果和医疗保健效率.
科学领域:
- 在瘤学瘤学.
- 医疗信息学 医疗信息学
- 营养科学 营养科学
背景情况:
- 营养不良影响高达80%的癌症患者,使治疗和治疗结果复杂化.
- 人工智能 (AI) 为瘤学中早期检测和个性化营养管理提供了潜在的解决方案.
- 系统性审查评估AI在识别和管理癌症患者营养不良方面的作用.
研究的目的:
- 系统地审查人工智能在评估,预测和监测癌症患者营养不良方面的有效性.
- 评估AI对瘤学临床结果和身体组成的影响.
- 综合关于人工智能在癌症护理营养管理中的应用证据.
主要方法:
- 在PubMed,Cochrane图书馆,CINAHL和EMBASE (2024年6月至7月) 的系统文献搜索.
- 包括关于人工智能干预癌症患者营养不良的定量初级研究.
- 使用乔安娜·布里格斯研究所工具进行质量评估,通过牛津EBM框架获得证据确定性.
主要成果:
- 分析了11项研究 (n=52,228),分类为评估/预测,结果和身体组成.
- 人工智能模型实现了营养不良的高预测准确性 (AUC>0.80),超过了传统工具.
- 深度学习改善了缓解症检测 (DSC 0.92-0.94);人工智能虚拟饮食师提高了坚持 (84%) 并减少了住院治疗.
结论:
- 人工智能在优化营养不良查,身体组成监测和癌症护理中的个性化营养干预方面显示出巨大的潜力.
- 整合人工智能可以提高患者的治疗效果,并优化瘤营养方面的资源配置.
- 需要进一步的研究来标准化AI模型的临床适用性.
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