Evidence map›Paper›PMID 41682235›Full record

ArticleHealthcare (Basel, Switzerland)2026

Transforming Public Health Practice with Artificial Intelligence: A Framework-Driven Approach.

Obinna O Oleribe, Florida Uzoaru, Adati Tarfa, Olabiyi H Olaniran, Simon D Taylor-Robinson

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Obinna O OleribeDepartment of Health Sciences, School of Public Health and Health Sciences, California State University, Dominguez Hills, 1000 E Victoria Street, Carson, CA 90747, USA.ORCID 0000-0002-9017-894X
Florida UzoaruCollege of Nursing and Health Sciences, Southeastern Louisiana University, Hammond, LA 70402, USA.ORCID 0000-0001-7507-6809
Adati TarfaDepartment of Internal Medicine, Yale School of Medicine, New Haven, CT 06511, USA.ORCID 0000-0002-8831-2396
Olabiyi H OlaniranDivision of Vascular & Endovascular Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA.ORCID 0009-0005-9864-4086
Simon D Taylor-RobinsonDepartment of Surgery and Cancer, St Mary's Hospital Campus, Imperial College London, London W2 1NY, UK.ORCID 0000-0002-8811-1834

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe emergence of artificial intelligence (AI) has triggered a global transformation, with the healthcare sector experiencing significant disruption and innovation. In current public health practice, AI is being deployed to power various aspects of public functions, including the assessment and monitoring of health, surveillance and disease control, health promotion and education, policy development and planning, health protection and regulation, prevention services, workforce development, community engagement and partnerships, emergency preparedness and response, and evaluation and research. Nevertheless, its use in leadership and management, such as in change management, process development and integration, problem solving, and decision-making, is still evolving.

aimThis study proposes the adoption of the IMPLICATIONS: AI holds immense potential to reshape public health by enabling personalized interventions, democratizing access to actionable data, supporting rapid and effective crisis response, advancing equity in health outcomes, promoting ethical and participatory public health practices, and strengthening environmental health and climate resilience. Achieving this goal will require a deliberate and proactive leadership vision, where public health leaders move beyond passive adoption to collaborate with AI specialists to co-create, co-design, co-develop, and co-deploy tools and resources tailored to the unique needs of public health practice. Call to action: Public health professionals can co-innovate in shaping AI evolution to ensure equitable, ethical, and value-based public health.

Indexed as

AI transparencyartificial intelligencebias and fairnessethicshealth equityhuman–AI collaborationpolicy developmentpublic health leadershippublic health practiceregulatory frameworks

Identifiers

PMID41682235
PMCPMC12897137

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.