关于医疗保健知识图的综述:资源,应用和承诺
Hejie Cui1, Jiaying Lu2, Ran Xu1
1Department of Computer Science, Emory University, Atlanta, GA, USA.
Journal of biomedical informatics
|July 25, 2025
概括
医疗保健知识图 (HKG) 结构医学知识用于研究和临床实践. 将HKG与大型语言模型 (LLM) 集成,可以提高它们在医疗保健中的应用和准确性.
科学领域:
- 生物医学信息学 生物医学信息学
- 医疗保健中的人工智能
背景情况:
- 医疗保健知识图 (HKG) 对于组织复杂的生物医学信息变得越来越重要.
- 现有关于HKG构造,利用和应用的文献需要综合.
研究的目的:
- 提供关于医疗保健知识图 (HKG) 现状的全面概述.
- 探索HKG的建造,利用模式和在医疗保健和生物医学研究中的应用.
主要方法:
- 使用谷歌学者对HKG进行系统的文献审查.
- 将纸张分类为HKG的构造,利用和应用.
- 分析无模型和基于模型的利用,并与大型语言模型 (LLM) 进行集成.
主要成果:
- 确定了关键主题:HKG的建设,利用和下游应用.
- 讨论了HKG发展的挑战和未来方向.
- 强调了HKG与LLMs的整合.
结论:
- HKG具有显著的潜力,可以影响生物医学研究和临床实践.
- 香港群体和LLM之间的协同作用为改善医疗保健应用提供了机会.
- 医疗基因组是构建医学知识的强大工具,指导未来的研究和开发.
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