Evidence map›Paper›PMID 40673212›Full record

ReviewFrontiers in artificial intelligence2025

Ethical-legal implications of AI-powered healthcare in critical perspective.

Mohammad Nasir, Kaif Siddiqui, Samreen Ahmed

Abstract readReview
In one paragraph

Review in Frontiers in artificial intelligence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
  2. Article
  3. Consensus statement on the application of artificial intelligence in osteoporosis screening and management: perspectives from the Asia-Pacific region.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2026
    Article
  4. Review
  5. Review
  6. Review
  7. Article
  8. Review
  9. Review
  10. Article
  11. 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

3 authors.

Mohammad NasirFaculty of Law, Aligarh Muslim University, Aligarh, India.
Kaif SiddiquiNALSAR University of Law, Hyderabad, India.
Samreen AhmedFaculty of Law, Aligarh Muslim University, Aligarh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing utilization of Artificial Intelligence (AI) systems in the field of healthcare, from diagnosis to medical decision making and patient care, necessitates identification of its potential benefits, risks and challenges. This requires an appraisal of AI use from a legal and ethical perspective. A review of the existing literature on AI in healthcare available on PubMed, Oxford Academic and Scopus revealed several common concerns regarding the relationship between AI, ethics, and healthcare-(i) the question of data: the choices inherent in collection, analysis, interpretation, and deployment of data inputted to and outputted by AI systems; (ii) the challenges to traditional patient-doctor relationships and long-held assumptions about privacy, identity and autonomy, as well as to the functioning of healthcare institutions. The potential benefits of AI's application need to be balanced against the legal-ethical issues emanating from its use-bias, consent, access, privacy and cost-to guard against detrimental effects of uncritical AI use. The authors suggest that a legal framework for AI should adopt a critical and grounded perspective-cognizant of the material political realities of AI and its wider impact on more marginalized communities. The largescale utilization of health datasets often without consent, responsibility or accountability, further necessitates regulation in the field of technology design, given the entwined nature of AI research with advancements in wearables and sensor technology. Taking into account the 'superhuman' and 'subhuman' traits of AI, regulation should aim to encourage the development of AI systems that augment rather than outrightly replace human effort.

Indexed as

AI-powered healthcareAI regulationaugmented intelligence (AI)health datalaw and AImedical privacy

Identifiers

PMID40673212
PMCPMC12263600

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.