Artificial intelligence applications in intracerebral hemorrhage care: implications for clinical and nursing practice - a narrative literature review

Little is known about how artificial intelligence tools are utilized across the different stages of intracerebral hemorrhage care or how they contribute to clinical decision-making and patient outcomes in this population. This narrative review aimed to explore current applications of artificial inte...

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Main Authors: Seoyoung Kim, Jungmin Lee, Soo-Hyun Nam
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Rehabilitation Sciences
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Online Access:https://www.frontiersin.org/articles/10.3389/fresc.2025.1620335/full
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author Seoyoung Kim
Jungmin Lee
Soo-Hyun Nam
author_facet Seoyoung Kim
Jungmin Lee
Soo-Hyun Nam
author_sort Seoyoung Kim
collection DOAJ
description Little is known about how artificial intelligence tools are utilized across the different stages of intracerebral hemorrhage care or how they contribute to clinical decision-making and patient outcomes in this population. This narrative review aimed to explore current applications of artificial intelligence in the clinical management of patients with intracerebral hemorrhage. A comprehensive search was conducted across five electronic databases (PubMed, CINAHL Plus with Full Text, Ovid MEDLINE, ProQuest, and Web of Science), supplemented by additional manual searches. This review included studies published in English between January 1, 2014, and December 31, 2024. Seven studies examining the application of artificial intelligence in the acute and post-acute phases of intracerebral hemorrhage care were included. In the acute phase, machine learning models such as Random Forest and XGBoost outperform traditional prognostic scoring systems, offering clinicians more precise tools for early risk stratification. In the post-acute phase, AI contributes to continuity of care by supporting data completion, rehabilitation planning, and remote rehabilitation, thereby enhancing patient-centered nursing practice with high predictive accuracy and practical utility. These findings suggest that artificial intelligence holds significant promise for enhancing prognosis prediction, clinical decision-making, and continuity of care in patients with intracerebral hemorrhage.
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spelling doaj-art-0f0a6b54ad7944dc82d092271a37481f2025-08-20T02:44:19ZengFrontiers Media S.A.Frontiers in Rehabilitation Sciences2673-68612025-07-01610.3389/fresc.2025.16203351620335Artificial intelligence applications in intracerebral hemorrhage care: implications for clinical and nursing practice - a narrative literature reviewSeoyoung Kim0Jungmin Lee1Soo-Hyun Nam2Department of Artificial Intelligence Convergence, Graduate School, Hallym University, Chuncheon, Republic of KoreaSchool of Nursing, Hallym University, Chuncheon, Republic of KoreaSchool of Nursing Science, Gyeongkuk National University, Andong, Republic of KoreaLittle is known about how artificial intelligence tools are utilized across the different stages of intracerebral hemorrhage care or how they contribute to clinical decision-making and patient outcomes in this population. This narrative review aimed to explore current applications of artificial intelligence in the clinical management of patients with intracerebral hemorrhage. A comprehensive search was conducted across five electronic databases (PubMed, CINAHL Plus with Full Text, Ovid MEDLINE, ProQuest, and Web of Science), supplemented by additional manual searches. This review included studies published in English between January 1, 2014, and December 31, 2024. Seven studies examining the application of artificial intelligence in the acute and post-acute phases of intracerebral hemorrhage care were included. In the acute phase, machine learning models such as Random Forest and XGBoost outperform traditional prognostic scoring systems, offering clinicians more precise tools for early risk stratification. In the post-acute phase, AI contributes to continuity of care by supporting data completion, rehabilitation planning, and remote rehabilitation, thereby enhancing patient-centered nursing practice with high predictive accuracy and practical utility. These findings suggest that artificial intelligence holds significant promise for enhancing prognosis prediction, clinical decision-making, and continuity of care in patients with intracerebral hemorrhage.https://www.frontiersin.org/articles/10.3389/fresc.2025.1620335/fullartificial intelligence (AI)intracerebral hemorrhage (ICH)machine learningprognosis predictionfunctional outcomerehabilitation
spellingShingle Seoyoung Kim
Jungmin Lee
Soo-Hyun Nam
Artificial intelligence applications in intracerebral hemorrhage care: implications for clinical and nursing practice - a narrative literature review
Frontiers in Rehabilitation Sciences
artificial intelligence (AI)
intracerebral hemorrhage (ICH)
machine learning
prognosis prediction
functional outcome
rehabilitation
title Artificial intelligence applications in intracerebral hemorrhage care: implications for clinical and nursing practice - a narrative literature review
title_full Artificial intelligence applications in intracerebral hemorrhage care: implications for clinical and nursing practice - a narrative literature review
title_fullStr Artificial intelligence applications in intracerebral hemorrhage care: implications for clinical and nursing practice - a narrative literature review
title_full_unstemmed Artificial intelligence applications in intracerebral hemorrhage care: implications for clinical and nursing practice - a narrative literature review
title_short Artificial intelligence applications in intracerebral hemorrhage care: implications for clinical and nursing practice - a narrative literature review
title_sort artificial intelligence applications in intracerebral hemorrhage care implications for clinical and nursing practice a narrative literature review
topic artificial intelligence (AI)
intracerebral hemorrhage (ICH)
machine learning
prognosis prediction
functional outcome
rehabilitation
url https://www.frontiersin.org/articles/10.3389/fresc.2025.1620335/full
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