ReviewCureus2024
Ethical Considerations in the Use of Artificial Intelligence and Machine Learning in Health Care: A Comprehensive Review.
Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 94 papers, 2 of them syntheses 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
94 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Artificial Intelligence in Cardiovascular Medicine: Focus on Hypertension.Hypertension (Dallas, Tex. : 1979) · 2026Pooled it
- AI-generated videos in medical education: systematic review.BMJ open quality · 2025Pooled it
- The Application of Artificial Intelligence in Public Health Surveillance in Portugal: An Exploratory Study of Expert Perspectives.Portuguese journal of public health · 2026Article
- Ethical Governance of Open Data Across Biomedical Research, Healthcare, and Public Health: Privacy, Equity, Trust, and Controlled Access.Health care analysis : HCA : journal of health philosophy and policy · 2026Article
- Neurofeedback for functional neurological disorders: future directions for research and clinical practice.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2026Review
- Artificial Intelligence in Pancreatic Endoscopic Ultrasonography: From Image-Based Diagnosis to Cytopathology.Journal of clinical medicine · 2026Review
- Ethical considerations of artificial intelligence in dementia research: a review of reviews.The Gerontologist · 2026Review
- Diabetes and Driving: How Predictive Technologies Will Alter Ethical and Legal Responsibilities.Journal of diabetes science and technology · 2026Article
- Non-inferiority analysis of a fetal heart rate artificial intelligence algorithm to registered nurse assessment.Pregnancy (Hoboken, N.J.) · 2026Article
- Evaluating sex bias in artificial intelligence-based echocardiographic analysis: a retrospective study on individuals with normal cardiac function and patients with systolic and diastolic dysfunction.Cardiovascular ultrasound · 2026Article
- Artificial Intelligence Scribes in Orthopaedic Surgery: A Narrative Review.Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews · 2026Review
- AI in Mental Health: Transforming Diagnosis and Management of Depression and Anxiety.Health science reports · 2026Article
- Revolutionizing Multimorbidity Care: A Narrative Review on Artificial Intelligence Applications.Health science reports · 2026Article
- Integrating Artificial Intelligence in Environmental Monitoring: A Paradigm Shift in Data-Driven Sustainability.EcoHealth · 2026Review
- The role of digital teaching methods in supporting practical skills training in the academic training of health professions - a scoping review.BMC medical education · 2026Article
- Evaluating ambient artificial intelligence documentation: effects on work efficiency, documentation burden, and patient-centered care.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Clinician and simulated patient perspectives on ambient AI scribes in psychiatric consultations: a qualitative study.Frontiers in psychiatry · 2026Article
- Feasibility of AI-driven disease surveillance systems at international airports in sub-Saharan Africa: a narrative review.Frontiers in public health · 2026Review
- Integrating AI, RNA Vaccines, and CAR-T Cells for Personalized Treatment.Journal of immunology research · 2026Review
- Dental Students' and Educators' Perceptions Toward the Adoption of Artificial Intelligence in Dental Education: A Survey-Based Study.International journal of dentistry · 2026Article
34 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
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) and machine learning (ML) technologies are revolutionizing health care by offering unprecedented opportunities to enhance patient care, optimize clinical workflows, and advance medical research. However, the integration of AI and ML into healthcare systems raises significant ethical considerations that must be carefully addressed to ensure responsible and equitable deployment. This comprehensive review explored the multifaceted ethical considerations surrounding the use of AI and ML in health care, including privacy and data security, algorithmic bias, transparency, clinical validation, and professional responsibility. By critically examining these ethical dimensions, stakeholders can navigate the ethical complexities of AI and ML integration in health care, while safeguarding patient welfare and upholding ethical principles. By embracing ethical best practices and fostering collaboration across interdisciplinary teams, the healthcare community can harness the full potential of AI and ML technologies to usher in a new era of personalized data-driven health care that prioritizes patient well-being and equity.
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.