ReviewJAMIA open2020
Use of machine learning in geriatric clinical care for chronic diseases: a systematic literature review.
Review in JAMIA open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 5 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
33 citing papers in PubMed, 5 syntheses or guidelines pooled it, 93 citations in OpenAlex.
- Nurse-led tele-palliative care for symptom management and family support: A hybrid umbrella review of reviews and primary studies.Palliative & supportive care · 2026Pooled it
- AI Quality Standards in Health Care: Rapid Umbrella Review.Journal of medical Internet research · 2024Pooled it
- Application of machine learning in measurement of ageing and geriatric diseases: a systematic review.BMC geriatrics · 2023Pooled it
- Application of machine learning approaches in predicting clinical outcomes in older adults - a systematic review and meta-analysis.BMC geriatrics · 2023Pooled it
- On usage of artificial intelligence for predicting mortality during and post-pregnancy: a systematic review of literature.BMC medical informatics and decision making · 2022Pooled it
- A clustering-based trajectory analytics of functional loss and recovery among older adults.PloS one · 2026Article
- Clinical and environmental factors, functional status, and multimorbidity-stratifying progression and prognosis of multimorbidity, frailty, and disability: the Age-It Research Program.The journals of gerontology. Series B, Psychological sciences and social sciences · 2025Article
- Comparison of Machine Learning Algorithms Identifying Children at Increased Risk of Out-of-Home Placement: Development and Practical Considerations.Health services research · 2025Article
- Prediction of early postoperative complications and transfusion risk after lumbar spinal stenosis surgery in geriatric patients: machine learning approach based on comprehensive geriatric assessment.BMC medical informatics and decision making · 2025Article
- The future of artificial intelligence in gerontological nursing in Saudi Arabia.BMC geriatrics · 2025Article
- Application of machine learning for early detection of chronic diseases in Africa.Journal of public health research · 2025Article
- Exploring Literature on Data Governance in the Health Care of Older Persons: Scoping Review.JMIR aging · 2025Article
- Hospital Artificial Intelligence/Machine Learning Adoption by Neighborhood Deprivation.Medical care · 2025Article
- The future of multimorbidity management in the older adults: transforming AI-enabled precision medicine.Frontiers in public health · 2025Review
- TrajVis: a visual clinical decision support system to translate artificial intelligence trajectory models in the precision management of chronic kidney disease.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- A scoping review of reporting gaps in FDA-approved AI medical devices.NPJ digital medicine · 2024Article
- Geriatrics and artificial intelligence in Spain (Ger-IA project): talking to ChatGPT, a nationwide survey.European geriatric medicine · 2024Observational
- Article
- New Horizons in artificial intelligence in the healthcare of older people.Age and ageing · 2023Article
- Machine learning functional impairment classification with electronic health record data.Journal of the American Geriatrics Society · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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 (
conclusionMore studies and ML standardization tailored to health care applications are required to confirm whether ML could aid in improving geriatric clinical care.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.