Evidence map›Paper›PMID 42374395›Full record

ArticleBMC medical ethics2026

Medical artificial intelligence and the right to health.

Sinead Prince, Serene Ong, Kathryn Lynn Muyskens, Julian Savulescu, Sebastian Porsdam Mann

Abstract read
In one paragraph

Article in BMC medical ethics, 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. Article
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.

Sinead PrinceCentre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Serene OngCentre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Kathryn Lynn MuyskensCentre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Julian SavulescuCentre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. julian.savulescu@uehiro.ox.ac.uk.
Sebastian Porsdam MannCentre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.

Funding

National Research Foundation Singapore AISG3-GV-2023-012National University of Singapore NUHSRO/2022/078/Startup/13Singapore Ministry of Health's National Medical Research Council under its Open Fund-Large Collaborative Grant OFLCG22may-0010Social Science Research Council (Singapore), administered by the Ministry of Education SSRC2023-SSRTG-006Wellcome Discovery 226801/Z/22/Z​Wellcome Trust
6 · The paper itself

Abstract

The international human right to health states that people have claims to access goods, services, and infrastructure that protects an adequate standard of health. The current and forthcoming advances in artificial intelligence (AI), which significantly improve the quality and efficacy of medical care, could raise the current standard of healthcare owed under the right to health. In this paper, we identify three duties owed under the right to health and describe ways in which AI can uniquely or more efficiently fulfill these duties, namely the duties to provide: access to good quality care that effectively improves patient health; equitable access to healthcare for all persons; and novel healthcare services that can only be achievable by medical AI. This paper will also consider some potential objections to our claim such as whether medical AI may undermine, rather than fulfil, the social determinants of health. We conclude that if medical AI can partially fulfil the right to health through increasing access and quality of healthcare, and if providing medical AI can be balanced against other obligations and rights, states will have corresponding duties to not unnecessarily restrict AI innovation through regulation and may even be required to invest in medical AI infrastructure to meet the right to health of their populations.

Indexed as

Artificial IntelligenceDelivery of Health CareHealth Services AccessibilityHuman RightsQuality of Health CareRight to HealthHumansSocial Determinants of HealthArtificial intelligenceHealthHealthcareHuman rights

Identifiers

PMID42374395
PMCPMC13579847

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.