ReviewChest2024
An Ethically Supported Framework for Determining Patient Notification and Informed Consent Practices When Using Artificial Intelligence in Health Care.
Review in Chest, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07762534 (A Randomized Controlled Trial Comparing Physician-Provided Versus Artificial Intelligence-Based Preoperative Counseling Before Elective Cesarean Delivery), which is not on this map. Cited by 19 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.
A Randomized Controlled Trial Comparing Physician-Provided Versus Artificial Intelligence-Based Preoperative Counseling Before Elective Cesarean Delivery
Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The evolving literature on the ethics of artificial intelligence for healthcare: a PRISMA scoping review.Frontiers in digital health · 2025Pooled it
- Dr. AI at the tumor board: what did we miss?International urology and nephrology · 2026Article
- Artificial Intelligence and the Ethical Foundations of Cardiothoracic Surgery: Evidence, Accountability, and the Limits of Delegated Judgment.Medical sciences (Basel, Switzerland) · 2026Review
- Effects of Type and Timing of Clinician-Facing AI Support on Patient Trust in Medical Consultations: 2 Vignette Experiments.Journal of medical Internet research · 2026Article
- Development and Deployment of DeepSeek-Based Applications in Healthcare: A Chinese Perspective.Health care science · 2026Article
- Trust As the Foundation for Informed Decision-Making in Prenatal Genetic Screening and Diagnostic Testing: A Qualitative Study.Health expectations : an international journal of public participation in health care and health policy · 2026Article
- Artificial intelligence for pediatric neuroimaging.Pediatric radiology · 2026Review
- Informed Consent Disclosures and Minimum Requirements in AI Clinical Trials: Cross-Sectional Analysis.Journal of medical Internet research · 2026Article
- Explainability and Human Oversight for AI-Generated Exercise Guidance in Digital Healthcare: A Governance-Oriented Narrative Review.Healthcare (Basel, Switzerland) · 2026Review
- Artificial intelligence in trauma care: applications, ethical challenges, and pathways toward responsible integration.Current opinion in anaesthesiology · 2026Article
- Me, my doctor and AI: a qualitative interview study on patients' requirements for trustworthy use of AI-CDSS in ophthalmology.BMJ digital health & AI · 2026Article
- Artificial intelligence in psychiatry: clinical applications, limitations, and ethical challenges.Frontiers in behavioral neuroscience · 2026Article
- Artificial Intelligence in Anesthesia: Enhancing Precision, Safety, and Global Access Through Data-Driven Systems.Journal of clinical medicine · 2025Review
- Navigating the challenges of artificial intelligence integration in thoracic surgery.Current challenges in thoracic surgery · 2025Article
- AI models in clinical neonatology: a review of modeling approaches and a consensus proposal for standardized reporting of model performance.Pediatric research · 2025Review
- Ethical Challenges and Current Opportunities of Artificial Intelligence in Cardiology.Avicenna journal of medicine · 2025Review
- Artificial Intelligence in Orthopedic Surgery: Current Applications, Challenges, and Future Directions.MedComm · 2025Review
- Patient information needs for transparent and trustworthy cardiovascular artificial intelligence: A qualitative study.PLOS digital health · 2025Article
- AI support in prehospital telemedicine: Perspectives of tele-emergency physicians and ethical considerations.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is increasingly being used in health care. Without an ethically supportable, standard approach to knowing when patients should be informed about AI, hospital systems and clinicians run the risk of fostering mistrust among their patients and the public. Therefore, hospital leaders need guidance on when to tell patients about the use of AI in their care. In this article, we provide such guidance. To determine which AI technologies fall into each of the identified categories (no notification or no informed consent [IC], notification only, and formal IC), we propose that AI use-cases should be evaluated using the following criteria: (1) AI model autonomy, (2) departure from standards of practice, (3) whether the AI model is patient facing, (4) clinical risk introduced by the model, and (5) administrative burdens. We take each of these in turn, using a case example of AI in health care to illustrate our proposed framework. As AI becomes more commonplace in health care, our proposal may serve as a starting point for creating consensus on standards for notification and IC for the use of AI in patient care.
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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.