TY - JOUR
T1 - Use of machine learning in geriatric clinical care for chronic diseases
T2 - A systematic literature review
AU - Choudhury, Avishek
AU - Renjilian, Emily
AU - Asan, Onur
N1 - Publisher Copyright:
VC The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association.
PY - 2020
Y1 - 2020
N2 - Objectives: Geriatric clinical care is a multidisciplinary assessment designed to evaluate older patients’ (age 65 years and above) functional ability, physical health, and cognitive well-being. The majority of these patients suffer from multiple chronic conditions and require special attention. Recently, hospitals utilize various artificial intelligence (AI) systems to improve care for elderly patients. The purpose of this systematic literature review is to understand the current use of AI systems, particularly machine learning (ML), in geriatric clinical care for chronic diseases. Materials and Methods: We restricted our search to eight databases, namely PubMed, WorldCat, MEDLINE, ProQuest, ScienceDirect, SpringerLink, Wiley, and ERIC, to analyze research articles published in English between January 2010 and June 2019. We focused on studies that used ML algorithms in the care of geriatrics patients with chronic conditions. Results: We identified 35 eligible studies and classified in three groups: psychological disorder (n ¼ 22), eye diseases (n ¼ 6), and others (n ¼ 7). This review identified the lack of standardized ML evaluation metrics and the need for data governance specific to health care applications. Conclusion: More studies and ML standardization tailored to health care applications are required to confirm whether ML could aid in improving geriatric clinical care.
AB - Objectives: Geriatric clinical care is a multidisciplinary assessment designed to evaluate older patients’ (age 65 years and above) functional ability, physical health, and cognitive well-being. The majority of these patients suffer from multiple chronic conditions and require special attention. Recently, hospitals utilize various artificial intelligence (AI) systems to improve care for elderly patients. The purpose of this systematic literature review is to understand the current use of AI systems, particularly machine learning (ML), in geriatric clinical care for chronic diseases. Materials and Methods: We restricted our search to eight databases, namely PubMed, WorldCat, MEDLINE, ProQuest, ScienceDirect, SpringerLink, Wiley, and ERIC, to analyze research articles published in English between January 2010 and June 2019. We focused on studies that used ML algorithms in the care of geriatrics patients with chronic conditions. Results: We identified 35 eligible studies and classified in three groups: psychological disorder (n ¼ 22), eye diseases (n ¼ 6), and others (n ¼ 7). This review identified the lack of standardized ML evaluation metrics and the need for data governance specific to health care applications. Conclusion: More studies and ML standardization tailored to health care applications are required to confirm whether ML could aid in improving geriatric clinical care.
KW - AI standards
KW - Artificial intelligence
KW - Chronic diseases
KW - Comorbidity
KW - Data governance
KW - Geriatric
KW - Machine learning
KW - Multimorbidity
KW - Older patients
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U2 - 10.1093/JAMIAOPEN/OOAA034
DO - 10.1093/JAMIAOPEN/OOAA034
M3 - Review article
AN - SCOPUS:85102079677
VL - 3
SP - 459
EP - 471
JO - JAMIA Open
JF - JAMIA Open
IS - 3
ER -