了解人工智能多种模型对癌症治疗的未来方法的能力
Hong Xu1, Chengyuan Yang2, Xiao-Yang Hu3
1Heilongjiang Academy of Traditional Chinese Medicine, Sanfu Road 142, Xiangfang District, Harbin, Heilongjiang, 150040, People's Republic of China.
概括
人工智能 (AI) 模型可以预测三阴性乳腺癌和软骨肉瘤的未来癌症治疗方法. 咨询多个AI工具可以帮助患者和医生了解各种治疗选择及其风险.
科学领域:
- 在瘤学瘤学.
- 人工智能的人工智能
- 医学教育 医学教育
背景情况:
- 人工智能 (AI) 在医学教育中越来越多地用于疾病治疗策略.
- 了解人工智能在预测未来癌症治疗方面的能力对患者,医生和科学家来说至关重要.
研究的目的:
- 探索AI模型在预测未来疾病治疗方法方面的教育价值.
- 评估人工智能在治疗三阴性乳腺癌 (TNBC) 和非分化软骨肉瘤 (DDCS) 等攻击性癌症方面应对现实世界的挑战的能力.
主要方法:
- 七个大型人工智能模型被要求预测和选择TNBC和DDCS的最佳未来治疗策略.
- 人工智能模型被要求提供支持证据,并概述对选择方法的临床试验计划.
- 总共有18个TNBC和34个DDCS的独特方法被生成和分析.
主要成果:
- 人工智能模型主要倾向于修饰的抗体-药物合物用于TNBC治疗.
- 联合免疫检查点抑制剂和IDH抑制剂是DDCS治疗的首选药物.
- 人工智能模型将CAR-T细胞疗法和基于CRISPR的基因编辑确定为高风险,高回报的方法.
结论:
- 人工智能模型展示了与当前癌症研究进展保持同步的能力.
- 利用多个AI模型可以增强对患者和临床医生不同癌症治疗方式的优缺点的理解.
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