临床实践中的人工智能:质量和证据
R Puchades1, L Ramos-Ruperto1,
1Grupo de trabajo de Medicina Digital de la Sociedad Española de Medicina Interna (SEMI); Servicio de Medicina Interna, Hospital Universitario La Paz, Madrid, Spain.
Revista clinica espanola
|November 7, 2024
概括
生成型人工智能 (AI) 在临床研究中快速发展,需要强有力的评估标准. 制定基于证据的AI (IABE) 准则对于确保医疗保健应用中的有效性和安全性至关重要.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能的人工智能
- 临床研究 临床研究
背景情况:
- 人工智能 (AI) 领域,特别是生成性AI,正在经历快速增长.
- 在科学出版物中,人工智能方法的使用量显著增加,这表明了潜在的潜力.
- 人工智能泡是一个泡.
- 需要对其临床应用进行批判性评估.
研究的目的:
- 强调在人工智能研究中需要标准和指导方针,特别是对于生成性人工智能.
- 强调基于证据的AI (IABE) 对于确保医疗保健中的有效性和安全的重要性.
主要方法:
- 在科学文献中审查人工智能应用的当前趋势.
- 对开发人工智能指南的现有和新兴举措进行分析 (例如,CONSORT AI,STARD AI,CHART协作).
主要成果:
- 生成性AI的出现需要新的框架来评估其在临床环境中的使用.
- 现有的指导方针侧重于歧视性AI,最近的努力是针对生成性AI.
结论:
- 科学监管和基于证据的AI (IABE) 对于保证医疗保健中AI应用的有效性和安全性至关重要.
- 建立明确的标准对于在人工智能的快速发展中保持护理质量至关重要.
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