@article{APM154364,
author = {Chunhong Xiao and Arie Nakhmani and Ashmita Thapa and Kimberly Kopecky and Joel G. Anderson and Robert L. Davis and Tami H. Wyatt and Niki Cobb and Cynthia J. Brown and J. Nicholas Odom and Avery C. Bechthold},
title = {Artificial intelligence in home-based serious illness care: a scoping review of applications supporting quality palliative care},
journal = {Annals of Palliative Medicine},
volume = {15},
number = {3},
year = {2026},
keywords = {},
abstract = {Artificial intelligence (AI) has emerged as a promising tool to address gaps in palliative care access and delivery for adults with serious illness and their family caregivers, particularly in home-based settings where access to specialty care is limited. AI-driven tools, including machine learning, natural language processing, and decision-support systems may enable proactive, personalized, and efficient approaches to addressing several domains of quality palliative care, as defined by the National Consensus Project (NCP), including continuity of care, symptom relief, emotional support, and family caregiver assistance. This scoping review aimed to systematically map the evidence on AI applications designed to assist home-based care for adults with serious illness and their family caregivers, with a focus on their potential role in enhancing palliative care delivery.},
issn = {2224-5839}, url = {https://apm.amegroups.org/article/view/154364}
}