通过自然语言处理推进风湿病学:从系统性审查中获得的见解和前景
Mahmud Omar1, Mohammad E Naffaa2, Benjamin S Glicksberg3,4
1Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel.
Rheumatology advances in practice
|October 14, 2024
概括
自然语言处理 (NLP) 和大语言模型 (LLM) 在风湿病学中显示出改善疾病检测和患者护理的前景. 需要进一步的研究来将这些先进的AI工具应用于更罕见的条件.
科学领域:
- 人工智能在医学中的应用
- 临床信息学 临床信息学
- 风湿病学研究 风湿病学研究
背景情况:
- 自然语言处理 (NLP) 和大型语言模型 (LLM) 正通过分析非结构化临床数据来改变医疗保健.
- 这些人工智能技术为从临床文本中提取见解提供了先进的方法.
研究的目的:
- 系统地审查NLP和LLM在风湿病学的应用.
- 评估它们在风湿病学领域的疾病检测,诊断和患者管理方面的潜力.
主要方法:
- 对七个数据库进行了系统审查.
- 包括评估NLP模型在风湿病学中的表现的原始研究文章.
- 数据提取和偏差风险评估遵循了PRISMA指南.
主要成果:
- 35项研究符合最初确定1491篇文章的纳入标准.
- NLP模型在检测类风湿性关节炎 (RA),脊椎关节炎 (SpAs) 和痛风方面表现出高准确性.
- 应用程序在疾病管理和预测疾病爆发方面显示出前景.
结论:
- 通过提高诊断准确性和个性化患者护理,NLP显著增强了类风湿病.
- 目前的应用程序对于RA和痛风等常见疾病来说已经得到了很好的发展.
- 进一步的研究是必要的,以解决局限性问题,并将NLP扩展到更罕见和复杂的类风湿病.
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