Foundation Models, Generative AI, and Large Language Models: Essentials for Nursing.
Journal
Computers, informatics, nursing : CIN
ISSN: 1538-9774
Titre abrégé: Comput Inform Nurs
Pays: United States
ID NLM: 101141667
Informations de publication
Date de publication:
01 May 2024
01 May 2024
Historique:
medline:
9
9
2024
pubmed:
9
9
2024
entrez:
9
9
2024
Statut:
epublish
Résumé
We are in a booming era of artificial intelligence, particularly with the increased availability of technologies that can help generate content, such as ChatGPT. Healthcare institutions are discussing or have started utilizing these innovative technologies within their workflow. Major electronic health record vendors have begun to leverage large language models to process and analyze vast amounts of clinical natural language text, performing a wide range of tasks in healthcare settings to help alleviate clinicians' burden. Although such technologies can be helpful in applications such as patient education, drafting responses to patient questions and emails, medical record summarization, and medical research facilitation, there are concerns about the tools' readiness for use within the healthcare domain and acceptance by the current workforce. The goal of this article is to provide nurses with an understanding of the currently available foundation models and artificial intelligence tools, enabling them to evaluate the need for such tools and assess how they can impact current clinical practice. This will help nurses efficiently assess, implement, and evaluate these tools to ensure these technologies are ethically and effectively integrated into healthcare systems, while also rigorously monitoring their performance and impact on patient care.
Identifiants
pubmed: 39248448
doi: 10.1097/CIN.0000000000001149
pii: 00024665-202405000-00011
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
377-387Informations de copyright
Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc.
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