由视网膜专家和基于大型语言模型的人工智能平台的糖尿病黄斑胀管理的建议
Ayushi Choudhary1, Nikhil Gopalakrishnan1, Aishwarya Joshi1
1Dept. of Retina and Vitreous, Narayana Nethralaya, #121/C, 1st R Block, Chord Road, Rajaji Nagar, 560010, Bengaluru, Karnataka, India.
International journal of retina and vitreous
|February 28, 2024
概括
人工智能 (AI) 在产生糖尿病黄斑 (DME) 管理建议方面表现有前途,与临床医生有适度的协议. 人工智能驱动的洞察力可能有助于改进全球DME治疗指南.
科学领域:
- 眼科医生 眼科 眼科
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 糖尿病黄斑 (DME) 是糖尿病患者视力丧失的主要原因.
- 有效管理DME至关重要,以防止不可逆转的视力损伤.
- 目前的管理准则需要根据不断变化的临床证据和技术进步不断更新.
研究的目的:
- 评估生成性人工智能 (AI) 在制定糖尿病黄斑 (DME) 管理建议中的作用.
- 在假设的案例场景中,将AI生成的建议与临床医生的反应进行比较.
- 评估AI和临床医生的建议是否符合国家DME管理准则.
主要方法:
- 人工智能根据患者的人口统计和临床数据生成了50个眼部病例场景.
- 对临床医师的反应,人工智能平台和对DME和眼部并发症管理的多数反应进行了计算.
- 建议与各种临床情况的印度国家指南进行了比较.
主要成果:
- 在临床医生和人工智能之间观察到中等到实质性的DME管理协议 (=0.60.69).
- 对眼部并发性疾病管理的共识不同,临床医生之间的共识较高 (=0.8),而不是AI (=0.360.49).
- 在特定的复杂案例中,AI/临床医生建议与国家指南之间的差异被发现.
结论:
- 这项研究开创了基于大型语言模型的生成AI用于DME管理建议的应用.
- 人工智能证明了对DME的临床决策支持的潜力.
- 调查结果可能有助于对全球DME管理准则的修订.
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