  Objectives-Geriatric clinical care is a multidisciplinary assessment designed
to evaluate older patients (age 65 years and above) functional ability,
physical health, and cognitive wellbeing. 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=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. Conclusion- More
studies and ML standardization tailored to health care applications are
required to confirm whether ML could aid in improving geriatric clinical care.
