Evidence map›Paper›PMID 42168479›Full record

ArticleNPJ digital medicine2026

The AI4GH community of practice: strengthening LMIC-Led artificial intelligence for global health.

Mylena Maria Guedes de Almeida, Mercedes Rumi, Marina Bowder, Prince Adjei, Bryain Maradiaga-Mendoza, Marina Albada, Adam Dale, Salvia Zeeshan, Simran Siraj, Nour El Arnaout and 5 more

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In one paragraph

Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

15 authors.

Mylena Maria Guedes de AlmeidaVisiting Student, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Mercedes RumiThe Global Health Network, University of Oxford, Oxford, UK.
Marina BowderThe Global Health Network, University of Oxford, Oxford, UK.
Prince AdjeiThe Global Health Network, University of Oxford, Oxford, UK.
Bryain Maradiaga-MendozaThe Global Health Network, University of Oxford, Oxford, UK.
Marina AlbadaThe Global Health Network, University of Oxford, Oxford, UK.
Adam DaleThe Global Health Network, University of Oxford, Oxford, UK.
Salvia ZeeshanThe Global Health Network, University of Oxford, Oxford, UK.
Simran SirajPHC Global, Karachi, Pakistan.
Nour El ArnaoutGlobal Health Institute, American University of Beirut, Beirut, Lebanon.
Rosalind Parkes-RatanshiSchool of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK.
Anneka WickramanayakeJacaranda Health, Nairobi, Kenya.
Peiling YapHealthAI - The Global Agency for Responsible AI in Health, Geneva, Switzerland.
Cintia CejasInstituto de Efectividad Clínica y Sanitaria, Buenos Aires, Argentina.
Trudie LangThe Global Health Network, University of Oxford, Oxford, UK. trudie.lang@ndm.ox.ac.uk.

Funding

International Development Research Centre 109950 - 001
6 · The paper itself

Abstract

Efforts to research, implement and scale responsible Artificial Intelligence (AI) for addressing health challenges in low- and middle-income countries (LMICs) are often fragmented. It limits collaboration and slows progress. Communities of Practice (CoPs) offer a promising approach to fostering shared learning and supporting the use of AI to strengthen health systems and improve health outcomes. The Artificial Intelligence for Global Health Community of Practice (AI4GH CoP), established in 2023, connects researchers, implementers and policymakers across the Global South to co-create and scale responsible AI solutions for public health priorities. This case study examines the design, functioning and outputs of the AI4GH CoP using a structured community roadmap. It illustrates a model for advancing responsible AI in LMICs by reinforcing local expertise and facilitating context-specific knowledge exchange and capacity building in ethical, regulatory and operational aspects of AI in global health. These lessons can inform the establishment of similar CoPs.

Identifiers

PMID42168479
PMCPMC13572545

What OpenQuestion holds

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Registered trials

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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.