Exploring the full potential of the electronic health record: the application of natural language processing for clinical practice.
Artificial Intelligence
Clinical Practice
Natural Language Processing
Journal
European journal of cardiovascular nursing
ISSN: 1873-1953
Titre abrégé: Eur J Cardiovasc Nurs
Pays: England
ID NLM: 101128793
Informations de publication
Date de publication:
24 Jun 2024
24 Jun 2024
Historique:
received:
02
04
2024
revised:
04
06
2024
accepted:
11
06
2024
medline:
24
6
2024
pubmed:
24
6
2024
entrez:
24
6
2024
Statut:
aheadofprint
Résumé
The electronic health record contains valuable patient data and offers opportunities to administer and analyze patients' individual needs longitudinally. However, most information in the electronic health record is currently stored in unstructured text notations. Natural Language Processing (NLP), a branch of artificial intelligence that enables computers to understand, interpret, and generate human language, can be used to delve into unstructured text data to uncover valuable insights and knowledge. This article discusses different types of NLP, the potential of NLP for cardiovascular nursing, and how to get started with NLP as a clinician.
Identifiants
pubmed: 38912955
pii: 7697888
doi: 10.1093/eurjcn/zvae091
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.