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

被引:13
|
作者
Nashwan, Abdulqadir J. [1 ]
Abujaber, Ahmad A. [1 ]
机构
[1] Hamad Med Corp, Nursing, Doha, Qatar
关键词
artificial intelligence; clinical decision-making; gpt-4; chatgpt; large language models; electronic health records;
D O I
10.7759/cureus.42634
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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.
引用
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页数:2
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