Evidence map›Paper›PMID 39398806›Full record

ArticleCureus2024

Doctor, Bot, or Both: Questioning the Medicolegal Liability of Artificial Intelligence in Indian Healthcare.

Satvik N Pai, Madhan Jeyaraman, Naveen Jeyaraman, Sankalp Yadav

Abstract readEditorial
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Review
  6. The Role of Artificial Intelligence in Improving the Public Health Care Delivery System in India: A Legal-Ethical Audit.Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine
    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

4 authors.

Satvik N PaiOrthopedics, PES University Institute of Medical Sciences and Research, Bengaluru, IND.
Madhan JeyaramanOrthopedics, South Texas Orthopedic Research Institute, Texas, USA.
Naveen JeyaramanOrthopedics, ACS Medical College and Hospital, Dr. M.G.R Educational and Research Institute, Chennai, IND.
Sankalp YadavMedicine, Shri Madan Lal Khurana Chest Clinic, New Delhi, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is rapidly transforming the landscape of healthcare, with its applications ranging from diagnostics to robotic surgery. As India swiftly integrates AI into its healthcare system, a critical question arises: who bears the liability when AI-driven medical decisions go wrong? This article explores the complexities of assigning legal responsibility for AI in healthcare, particularly within the Indian context. While India's legal framework, including the Information Technology Act, intersects with AI usage, it lacks specific provisions addressing AI liability. The National Strategy for AI, although a step forward, does not resolve the ambiguities surrounding accountability. The article also examines how other countries, particularly the European Union and the United States, are beginning to tackle these challenges through proposed directives and regulations. However, the absence of clear, comprehensive laws worldwide reflects the inherent difficulties in legislating AI stemming from its autonomous nature, the "black box" problem, and the multifaceted roles of stakeholders. Until robust legal frameworks are established, the article cautions healthcare professionals to exercise vigilance when using AI tools, recognizing that they may still bear significant liability. This evolving legal landscape underscores the need for continued deliberations in AI regulations.

Indexed as

artificial intelligencehealthcareindian healthcareliabilitymedicolegal

Identifiers

PMID39398806
PMCPMC11470824

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.