ArticleArchives of medical sciences. Atherosclerotic diseases2026
Artificial intelligence in preventive care in primary health care settings: a scoping review.
Article in Archives of medical sciences. Atherosclerotic diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Artificial Intelligence in Cardiovascular Risk Prediction: An Up-to-Date Narrative Review on the Emerging Role of Lipid Profile-Based Models.Journal of clinical medicine · 2026Review
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) could be integrated into Primary Health Care (PHC) to enhance the preventive care of several diseases. This scoping review aims to provide current evidence on AI applications for the prevention of non-infectious diseases in PHC. A structured search was conducted in PubMed/Medline and Scopus databases to identify studies evaluating AI-based interventions implemented in the preventive care of non-infectious diseases in the PHC sector. AI-supported preventive care was compared to standard preventive care or non-AI-based interventions. Preventive medicine was defined as at least one primary outcome related to disease incidence, risk reduction, and early detection rates of non-infectious diseases. AI demonstrates significant potential in preventive medicine in PHC as it enables proactive, personalized, and data-driven interventions. However, its adoption requires strategies to overcome technical, ethical, and organizational barriers. Future research should address real-world implementation, cost-effectiveness, and clinician engagement to maximize clinical impact.
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Registered trials
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