ArticlePLOS digital health2025
Ethical challenges and evolving strategies in the integration of artificial intelligence into clinical practice.
Article in PLOS digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 92 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
92 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review on the generative AI applications in human medical genetics.Frontiers in genetics · 2025Pooled it
- AI Trustworthiness in the Perioperative Period for Patients with Serious Illness: Scoping Narrative Review.JMIR perioperative medicine · 2026Article
- Beyond robotic platforms: artificial intelligence and the emergence of intelligent surgical ecosystems in colorectal surgery.Journal of robotic surgery · 2026Review
- Artificial Intelligence and Algorithmic Bias in Burn Care: A Literature Review of Ethical Challenges.Journal of burn care & research : official publication of the American Burn Association · 2026Review
- Review
- Psychometric Evaluation of the Artificial Intelligence Perception Scale for Cancer Patients: A Structural Equation Modeling Approach.Journal of evaluation in clinical practice · 2026Article
- From prediction to practice: closing the translation gap in artificial intelligence for anesthesia.Journal of clinical monitoring and computing · 2026Review
- Physiological Data Integration and Predictive Modeling in Intensive Care.Life (Basel, Switzerland) · 2026Review
- Mapping National Governance of AI for Health: Protocol for a Global Scoping Review.JMIR research protocols · 2026Article
- Multilingual Voice AI for Postoperative Cataract Follow-Up in Turkish Speaking Patients in the United Kingdom: Patient and Public Involvement Focus Group Study.JMIR formative research · 2026Article
- Ethical and Governance Challenges of AI in Medical Imaging and Diagnostics: A Systematic Survey and Policy Framework Recommendations.Healthcare (Basel, Switzerland) · 2026Review
- From Concept to Conditions of Practice: Digital Empathy Must be Designed, Taught, and Protected.Nursing inquiry · 2026Article
- Artificial intelligence and predictive tools in non-muscle invasive bladder cancer: a narrative review of current insights and advances.Translational andrology and urology · 2026Review
- Next-generation biomedical nanorobots: active design, intelligent control, and translational opportunities in regenerative and minimally invasive medicine.Journal of nanobiotechnology · 2026Review
- Human-AI Interaction in Interventional Radiology: A Narrative Review of Current Applications, Challenges, and Future Directions.Journal of imaging · 2026Review
- Ethical Governance of Large Language Models in Health Care: Trust, Responsibility, and Equity in Routine Use.Journal of medical Internet research · 2026Article
- AI in Drug Discovery: Clinical Failures, Regulatory Reality, and the Validation Crisis Behind the Hype.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Educational Frameworks for Diagnostic Decision-Making in AI-Enhanced Head and Neck Pathology.Head and neck pathology · 2026Review
- From Bench to Bedside: The Path Toward Real-World Translation for Artificial Intelligence in Pancreatic Cancer Detection.Korean journal of radiology · 2026Review
- Artificial Intelligence in Peripheral Artery Disease: A Science Advisory From the American Heart Association.Circulation. Population health and outcomes · 2026Review
32 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has rapidly transformed various sectors, including healthcare, where it holds the potential to transform clinical practice and improve patient outcomes. However, its integration into medical settings brings significant ethical challenges that need careful consideration. This paper examines the current state of AI in healthcare, focusing on five critical ethical concerns: justice and fairness, transparency, patient consent and confidentiality, accountability, and patient-centered and equitable care. These concerns are particularly pressing as AI systems can perpetuate or even exacerbate existing biases, often resulting from non-representative datasets and opaque model development processes. The paper explores how bias, lack of transparency, and challenges in maintaining patient trust can undermine the effectiveness and fairness of AI applications in healthcare. In addition, we review existing frameworks for the regulation and deployment of AI, identifying gaps that limit the widespread adoption of these systems in a just and equitable manner. Our analysis provides recommendations to address these ethical challenges, emphasizing the need for fairness in algorithm design, transparency in model decision-making, and patient-centered approaches to consent and data privacy. By highlighting the importance of continuous ethical scrutiny and collaboration between AI developers, clinicians, and ethicists, we outline pathways for achieving more responsible and inclusive AI implementation in healthcare. These strategies, if adopted, could enhance both the clinical value of AI and the trustworthiness of AI systems among patients and healthcare professionals, ensuring that these technologies serve all populations equitably.
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.