This paper is in the following e-collection/theme issue:

Theme Issue 2022: Health Natural Language Processing and Applications (CHIP) (27) Natural Language Processing (801) Machine Learning (1730) Decision Support for Health Professionals (1337) Artificial Intelligence (1723)

Published on in Vol 10, No 12 (2022): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38161, first published .
Boosting Delirium Identification Accuracy With Sentiment-Based Natural Language Processing: Mixed Methods Study

Boosting Delirium Identification Accuracy With Sentiment-Based Natural Language Processing: Mixed Methods Study

Boosting Delirium Identification Accuracy With Sentiment-Based Natural Language Processing: Mixed Methods Study

Authors of this article:

Lu Wang1, 2 Author Orcid Image ;   Yilun Zhang1 Author Orcid Image ;   Mark Chignell1 Author Orcid Image ;   Baizun Shan1 Author Orcid Image ;   Kathleen A Sheehan3, 4 Author Orcid Image ;   Fahad Razak3, 5 Author Orcid Image ;   Amol Verma3, 5 Author Orcid Image
Article Authors Cited by (13) Tweetations (3) Metrics

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  10. Traynor V, Ho B, Bimrose J, Riegel M, Chiu H, Boehm L, Hayter M, Neville S. Nurses Must Improve Delirium Care: A Call to Action. Journal of Clinical Nursing 2025 View
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  1. Chen A, Paredes D, Yu Z, Lou X, Brunson R, Thomas J, Martinez K, Lucero R, Magoc T, Solberg L, Snigurska U, Ser S, Prosperi M, Bian J, Bjarnadottir R, Wu Y. 2024 IEEE 12th International Conference on Healthcare Informatics (ICHI). Identifying Symptoms of Delirium from Clinical Narratives Using Natural Language Processing View