Leveraging Artificial Intelligence/Machine Learning Models to Identify Potential Palliative Care Beneficiaries: A Systematic Review

Toby Bressler; Jiyoun Song; Vijayvardhan Kamalumpundi; Sena Chae; Hyunjin Song

doi:10.3928/00989134-20241210-01

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Leveraging Artificial Intelligence/Machine Learning Models to Identify Potential Palliative Care Beneficiaries: A Systematic Review

Journal article

Peer reviewed

Leveraging Artificial Intelligence/Machine Learning Models to Identify Potential Palliative Care Beneficiaries: A Systematic Review

Toby Bressler, Jiyoun Song, Vijayvardhan Kamalumpundi, Sena Chae and Hyunjin Song

Journal of gerontological nursing, Vol.51(1), pp.7-14

01/01/2025

DOI: 10.3928/00989134-20241210-01

PMID: 39746126

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Abstract

Purpose The current review examined the application of artificial intelligence (AI) and machine learning (ML) techniques in palliative care, specifically focusing on models used to identify potential beneficiaries of palliative services among individuals with chronic and terminal illnesses. Methods A systematic review was conducted across four electronic databases. Five studies met inclusion criteria, all of which applied AI/ML models to predict outcomes relevant to palliative care, such as mortality or the need for services. Results Of 1,504 studies screened, five studies used supervised ML algorithms, whereas one used natural language processing with a deep learning model to identify potential palliative care candidates. The most common AI/ML algorithms included neural network–based models, logistic regression, and tree-based models. Conclusion AI and ML models offer promising avenues for identifying palliative care beneficiaries. As AI continues to evolve, its potential to reshape palliative care through early identification is significant, providing opportunities for timely and targeted care interventions. [Journal of Gerontological Nursing, 51(1), 7–14.]

Chronic Illnesses

Palliative Care

Artificial intelligence

Mortality

Neural networks

Details

Title: Subtitle: Leveraging Artificial Intelligence/Machine Learning Models to Identify Potential Palliative Care Beneficiaries: A Systematic Review
Creators: Toby Bressler - Mount Sinai Health System
Jiyoun Song - University of Pennsylvania
Vijayvardhan Kamalumpundi - Mayo Clinic
Sena Chae - University of Iowa
Hyunjin Song - Trinity School of Medicine
Resource Type: Journal article
Publication Details: Journal of gerontological nursing, Vol.51(1), pp.7-14
DOI: 10.3928/00989134-20241210-01
PMID: 39746126
NLM abbreviation: J Gerontol Nurs
ISSN: 0098-9134
eISSN: 1938-243X
Publisher: SLACK INCORPORATED
Language: English
Date published: 01/01/2025
Academic Unit: Nursing
Record Identifier: 9984769792002771

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