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利用大语言模型(LLMs)的力量优化电子健康记录(EHRs)

Harnessing the Power of Large Language Models (LLMs) for Electronic Health Records (EHRs) Optimization.

作者信息

Nashwan Abdulqadir J, AbuJaber Ahmad A

机构信息

Nursing, Hamad Medical Corporation, Doha, QAT.

出版信息

Cureus. 2023 Jul 29;15(7):e42634. doi: 10.7759/cureus.42634. eCollection 2023 Jul.

Abstract

This editorial discusses the potential benefits of integrating large language models (LLMs), such as GPT-4, into electronic health records (EHRs) to optimize patient care, improve clinical decision-making, and promote efficient healthcare management. Artificial intelligence (AI)-driven LLMs can revolutionize healthcare practices by streamlining the data input process, expediting information extraction from unstructured narratives, and facilitating personalized patient communication. However, concerns related to patient privacy, data security, and potential biases must be addressed to ensure equitable healthcare for all. Therefore, we encourage healthcare professionals and researchers to explore innovative solutions that leverage AI capabilities while addressing the challenges associated with privacy and equity.

摘要

这篇社论讨论了将诸如GPT-4等大语言模型(LLMs)集成到电子健康记录(EHRs)中的潜在益处,以优化患者护理、改善临床决策并促进高效的医疗管理。人工智能(AI)驱动的大语言模型可以通过简化数据输入过程、加快从非结构化叙述中提取信息以及促进个性化患者沟通来彻底改变医疗实践。然而,必须解决与患者隐私、数据安全和潜在偏差相关的问题,以确保为所有人提供公平的医疗服务。因此,我们鼓励医疗专业人员和研究人员探索创新解决方案,在利用人工智能能力的同时应对与隐私和公平相关的挑战。

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