Acute on chronic liver failure: prognostic models and artificial intelligence applications.
Journal
Hepatology communications
ISSN: 2471-254X
Titre abrégé: Hepatol Commun
Pays: United States
ID NLM: 101695860
Informations de publication
Date de publication:
01 04 2023
01 04 2023
Historique:
received:
19
07
2022
accepted:
04
01
2023
medline:
29
3
2023
entrez:
27
3
2023
pubmed:
28
3
2023
Statut:
epublish
Résumé
Critically ill patients presenting with acute on chronic liver failure (ACLF) represent a particularly vulnerable population due to various considerations surrounding the syndrome definition, lack of robust prospective evaluation of outcomes, and allocation of resources such as organs for transplantation. Ninety-day mortality related to ACLF is high and patients who do leave the hospital are frequently readmitted. Artificial intelligence (AI), which encompasses various classical and modern machine learning techniques, natural language processing, and other methods of predictive, prognostic, probabilistic, and simulation modeling, has emerged as an effective tool in various areas of healthcare. These methods are now being leveraged to potentially minimize physician and provider cognitive load and impact both short-term and long-term patient outcomes. However, the enthusiasm is tempered by ethical considerations and a current lack of proven benefits. In addition to prognostic applications, AI models can likely help improve the understanding of various mechanisms of morbidity and mortality in ACLF. Their overall impact on patient-centered outcomes and countless other aspects of patient care remains unclear. In this review, we discuss various AI approaches being utilized in healthcare and discuss the recent and expected future impact of AI on patients with ACLF through prognostic modeling and AI-based approaches.
Identifiants
pubmed: 36972378
doi: 10.1097/HC9.0000000000000095
pii: 02009842-202304010-00015
pmc: PMC10043584
pii:
doi:
Types de publication
Review
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Association for the Study of Liver Diseases.
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