医疗保健中的生成人工智能:对益处,挑战和应用的范围审查
Khadijeh Moulaei1, Atiye Yadegari2, Mahdi Baharestani3
1Department of Health Information Technology, School of Paramedical, Ilam University of Medical Sciences, Ilam, Iran.
International journal of medical informatics
|May 11, 2024
概括
生成型人工智能 (GAI) 提供了重要的医疗保健好处,如改善诊断和信息获取. 然而,为了安全实施,必须解决不准确的内容和未经验证的来源等挑战.
科学领域:
- 医疗保健信息学 医疗保健信息学
- 人工智能在医学中的应用
- 数字健康数字健康
背景情况:
- 生成型人工智能 (GAI) 正在通过提供新的诊断,治疗和患者护理解决方案来改变医疗保健.
- 将GAI整合到医疗保健中需要对其多样化的应用,潜在的好处和固有的挑战有充分的了解.
研究的目的:
- 对医疗保健领域的生成人工智能 (GAI) 应用进行全面的范围审查.
- 确定和综合与在医疗保健环境中使用GAI相关的主要好处和挑战.
主要方法:
- 使用主要科学数据库进行了系统范围审查:科学网络,PubMed和Scopus.
- 研究选择遵循PRISMA-ScR指南,涉及严格选标题,摘要和全文文章.
- 数据提取的重点是确定医疗保健领域内的GAI模型,应用,好处和挑战.
主要成果:
- 在最初的1406篇文章中,包括了109篇,揭示了在医疗保健中使用的九种不同的GAI模型.
- 聊天GPT,谷歌Bard (Gemini) 和微软Bing AI是最常使用的模型.
- 主要应用包括提供健康信息,帮助疾病诊断和预测. 主要的好处是快速获取信息和提高诊断准确度,与不准确的内容生成和未经验证的来源所带来的挑战形成对比.
结论:
- 本综述综合了GAI在医疗保健中的应用,好处和挑战的现状.
- GAI 具有对医疗保健的变革潜力,但解决其局限性,特别是内容准确性和来源验证,对于负责任的采用至关重要.
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