ReviewDigital health
Medical artificial intelligence ethics: A systematic review of empirical studies.
Review in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 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
73 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Examining inclusivity: the use of AI and diverse populations in health and social care: a systematic review.BMC medical informatics and decision making · 2025Pooled it
- Telehealth and access to acute primary care in Europe: Balancing opportunity and equity.The European journal of general practice · 2026Article
- Article
- Veritas amid Post-truth: Catholic Ethics and the Moral Conditions of Philippine Public Health.Journal of religion and health · 2026Article
- From principle to practice: Developing a digital-age clinical artificial intelligence ethics competence framework through early-career doctors' experiences.Medical education · 2026Article
- Investigating the Potential Effects of Medical AI Systems on Physician Autonomy: Pretest of a Semistructured Qualitative Interview Guide.JMIR formative research · 2026Article
- Article
- The Future of Artificial Intelligence in Emergency Medical Services by 2030: An International Consensus Report.Journal of the American College of Emergency Physicians open · 2026Article
- Implementation of artificial intelligence in palliative and supportive care for people with cancer: A scoping review.Palliative medicine · 2026Article
- Machine learning and deep learning models for predicting colorectal cancer metastases: A comprehensive review.European journal of radiology open · 2026Review
- Patients' Perspectives on the Implementation of AI in Radiological Diagnostics: Focus Group Study.Journal of medical Internet research · 2026Article
- Cognitive differences and ethical concerns in artificial intelligence in healthcare: a comparative text mining study of public and healthcare professional discussions.BMC medical ethics · 2026Article
- Examining developer perspectives on medical AI regulatory frameworks.NPJ digital medicine · 2026Article
- Attitudes Towards the Use of Artificial Intelligence in Healthcare: A Conjoint Analysis Survey in Singapore.Asian bioethics review · 2026Article
- The Ethics of Leveraging Routinely Collected Patient Data for AI Development: Mixed Methods Study.Journal of medical Internet research · 2026Article
- Exploring the Balance Between Artificial Intelligence and Human Expertise in Shaping Breast Reconstruction Outcomes: A Comparative Reflection Study.Journal of clinical medicine · 2026Article
- Ethical Knowledge, Challenges, and Institutional Strategies Among Medical AI Developers and Researchers: Focus Group Study.Journal of medical Internet research · 2026Article
- Refining AI's role in colorectal cancer screening education: a reply addressing nuances of bias and comprehensive validation.International journal of surgery (London, England) · 2026Article
- Operationalising Inclusion for Participatory Design: Worked Examples for TRIPOD+AI & PROBAST+AI.Health services insights · 2026Article
- Ethical integration of patient-reported outcomes and digital biomarkers in AI healthcare models: an expert consensus framework.Frontiers in digital health · 2026Article
13 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
3 authors.
Funding
Abstract
Background: Artificial intelligence (AI) technologies are transforming medicine and healthcare. Scholars and practitioners have debated the philosophical, ethical, legal, and regulatory implications of medical AI, and empirical research on stakeholders' knowledge, attitude, and practices has started to emerge. This study is a systematic review of published empirical studies of medical AI ethics with the goal of mapping the main approaches, findings, and limitations of scholarship to inform future practice considerations. Methods: We searched seven databases for published peer-reviewed empirical studies on medical AI ethics and evaluated them in terms of types of technologies studied, geographic locations, stakeholders involved, research methods used, ethical principles studied, and major findings. Findings: Thirty-six studies were included (published 2013-2022). They typically belonged to one of the three topics: exploratory studies of stakeholder knowledge and attitude toward medical AI, theory-building studies testing hypotheses regarding factors contributing to stakeholders' acceptance of medical AI, and studies identifying and correcting bias in medical AI. Interpretation: There is a disconnect between high-level ethical principles and guidelines developed by ethicists and empirical research on the topic and a need to embed ethicists in tandem with AI developers, clinicians, patients, and scholars of innovation and technology adoption in studying medical AI ethics.
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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.