ReviewInteractive journal of medical research2024
Benefits and Risks of AI in Health Care: Narrative Review.
Review in Interactive journal of medical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 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
80 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Integrated Multimodal Approaches in Pediatric Palliative Oncology: A Systematic Review Focused on Infants and Toddlers.In vivo (Athens, Greece)Pooled it
- Effects of artificial intelligence based physiotherapy educational approach in developing clinical reasoning skills: a randomized controlled trial.BMC medical education · 2025Trial
- Beyond Traditional Risk Scores: Artificial Intelligence in Coronary Plaque Characterization and Personalized Atherosclerosis Management.Journal of cardiovascular development and disease · 2026Review
- Artificial Intelligence for Clinical Decision Support in Rural Spine Care: A Narrative Review.Healthcare (Basel, Switzerland) · 2026Review
- Article
- The AI-Driven Healthcare Value Framework-Rethinking Traditional Care Models in the Age of Automation.Healthcare (Basel, Switzerland) · 2026Article
- Analysis of ICU Nurses' Needs for Intelligent Excreta Nursing Robots: A Multicenter Cross-Sectional Study in China.Healthcare (Basel, Switzerland) · 2026Article
- Endothelial Continuum and Capillary Specialization in Pulmonary Vascular Development.Arteriosclerosis, thrombosis, and vascular biology · 2026Review
- 1,357 AI medical devices cleared, 3 actually tested on patient outcomes.PLOS digital health · 2026Review
- A stacking based deep learning framework integrating random search neural architecture search for meniscus tear diagnosis.Journal of applied clinical medical physics · 2026Article
- PROACTIVE-AI: An Intelligent Dashboard for Assessing and Predicting of FDA-approved AI Software Performance in Real-World Clinical Scenarios.Research square · 2026Article
- Automatic acromegaly detection using deep learning on hand images: a multicenter observational study.The Journal of clinical endocrinology and metabolism · 2026Observational
- Artificial Intelligence in Social Health: A Narrative Review of Uses, Advantages, Challenges, and Future Directions.Healthcare (Basel, Switzerland) · 2026Review
- The trust in AI-generated health advice (TAIGHA) scale and short version (TAIGHA-S): Development and validation study.PLOS digital health · 2026Article
- Public health informatics tools for dengue risk management: A systematic review.PLOS digital health · 2026Article
- Transparency in healthcare AI: Testing EU regulatory provisions against users' transparency needs.PLOS digital health · 2026Article
- Lessons from Smart Cart 2.0: Considerations for Integrating Purchasing Data into Healthy Eating Interventions with AI Approaches.The Journal of nutrition · 2026Article
- Article
- Beyond Algorithmic Oversight: Internal Morality of Medicine and Meaningful Human Control in AI-Assisted Care.Healthcare (Basel, Switzerland) · 2026Article
- Exploring Student Perceptions of Generative AI Therapists and Their Benefits and Challenges in Schools.International journal of psychology : Journal international de psychologie · 2026Article
20 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe integration of artificial intelligence (AI) into health care has the potential to transform the industry, but it also raises ethical, regulatory, and safety concerns. This review paper provides an in-depth examination of the benefits and risks associated with AI in health care, with a focus on issues like biases, transparency, data privacy, and safety.
objectiveThis study aims to evaluate the advantages and drawbacks of incorporating AI in health care. This assessment centers on the potential biases in AI algorithms, transparency challenges, data privacy issues, and safety risks in health care settings.
methodsStudies included in this review were selected based on their relevance to AI applications in health care, focusing on ethical, regulatory, and safety considerations. Inclusion criteria encompassed peer-reviewed articles, reviews, and relevant research papers published in English. Exclusion criteria included non-peer-reviewed articles, editorials, and studies not directly related to AI in health care. A comprehensive literature search was conducted across 8 databases: OVID MEDLINE, OVID Embase, OVID PsycINFO, EBSCO CINAHL Plus with Full Text, ProQuest Sociological Abstracts, ProQuest Philosopher's Index, ProQuest Advanced Technologies & Aerospace, and Wiley Cochrane Library. The search was last updated on June 23, 2023. Results were synthesized using qualitative methods to identify key themes and findings related to the benefits and risks of AI in health care.
resultsThe literature search yielded 8796 articles. After removing duplicates and applying the inclusion and exclusion criteria, 44 studies were included in the qualitative synthesis. This review highlights the significant promise that AI holds in health care, such as enhancing health care delivery by providing more accurate diagnoses, personalized treatment plans, and efficient resource allocation. However, persistent concerns remain, including biases ingrained in AI algorithms, a lack of transparency in decision-making, potential compromises of patient data privacy, and safety risks associated with AI implementation in clinical settings.
conclusionsIn conclusion, while AI presents the opportunity for a health care revolution, it is imperative to address the ethical, regulatory, and safety challenges linked to its integration. Proactive measures are required to ensure that AI technologies are developed and deployed responsibly, striking a balance between innovation and the safeguarding of patient well-being.
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.