ArticleCureus2024
Doctor, Bot, or Both: Questioning the Medicolegal Liability of Artificial Intelligence in Indian Healthcare.
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.
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.
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.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Enhanced fracture detection on radiographs with AI assistance for clinicians: a systematic review and meta-analysis.Annals of medicine · 2026Pooled it
- Artificial intelligence and robotic technologies redefining precision and personalization in orthopedic surgery: a narrative review.Frontiers in bioengineering and biotechnology · 2026Review
- Artificial Intelligence in Orthopedic Surgery: Current Applications, Challenges, and Future Directions.MedComm · 2025Review
- Surgery without distance: will 5G-based robot-assisted telesurgery redefine modern surgery?Translational lung cancer research · 2025Review
- Ethical-legal implications of AI-powered healthcare in critical perspective.Frontiers in artificial intelligence · 2025Review
- 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 MedicineReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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
Identifiers
What OpenQuestion holds
Registered trials
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.