ReviewCureus2026
Addressing Bias, Privacy, Security, and Patient Autonomy in Artificial Intelligence (AI)-Driven Healthcare: A Review of Current Guidelines.
Review in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Construction of an e-Health Literacy Program for Patients with Obstructive Sleep Apnea-Hypopnea Syndrome Based on Integrative Model of eHealth Use.Nature and science of sleep · 2026Article
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
Integrating artificial intelligence (AI) in healthcare has revolutionized patient care, diagnostics, and operational efficiency. However, the reliance of AI systems on vast amounts of personal data raises significant concerns regarding data privacy, security, and ethical governance. This narrative review examines global regulations, including the General Data Protection Regulation, the Health Insurance Portability and Accountability Act, and Organization for Economic Co-operation and Development guidelines, and contrasts them with India's evolving data privacy landscape, particularly under the Digital Personal Data Protection Act, 2023. The review explores key ethical challenges, including AI bias, patient consent, data security, and algorithmic transparency, and provides case studies from around the world. The paper concludes with policy recommendations to harmonize international standards, strengthen AI governance in healthcare, and foster ethical AI development.
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.