Abstract
ObjectivesGeriatric 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 MethodsWe 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.ResultsWe identified 35 eligible studies and classified in three groups: psychological disorder (n = 22), eye diseases (n = 6), and others (n = 7). This review identified the lack of standardized ML evaluation metrics and the need for data governance specific to health care applications.ConclusionMore studies and ML standardization tailored to health care applications are required to confirm whether ML could aid in improving geriatric clinical care.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
