ReviewNature biomedical engineering2023
Algorithmic fairness in artificial intelligence for medicine and healthcare.
Review in Nature biomedical engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 316 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
316 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Artificial Intelligence Applications in Medical Devices for Personalized Health Care Solutions: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Advancements in artificial intelligence transforming medical education: a comprehensive overview.Medical education online · 2025Pooled it
- Artificial intelligence and extracellular vesicles in oncology: towards tumor diagnosis, prediction, and therapy.Drug delivery · 2026Review
- Collaborative artificial intelligence for the diagnosis and management of acute ischemic stroke.Annals of medicine · 2026Review
- Mitigating Domain Shift and Dataset Bias in Deep Learning Models for Cancer Diagnostics.Journal of imaging informatics in medicine · 2026Review
- The Influence of Large Language Model-Generated Artificial Intelligence Risk Estimates on Clinical Decision-Making in Breast Imaging: A Simulation-Based Study.Diagnostics (Basel, Switzerland) · 2026Article
- Artificial Intelligence in Photodynamic Therapy: From Molecular Design of Photosensitizers to Intelligent Delivery, Adaptive Dosimetry, and Personalized Prognostication of Results.International journal of molecular sciences · 2026Review
- Artificial intelligence in cardiovascular medicine: a practical guide for clinicians and researchers.European heart journal. Digital health · 2026Review
- Refined Exclusion in Medical AI: Data Justice and Patient Safety Governance.Journal of medical Internet research · 2026Article
- Application of artificial intelligence in early warning, diagnosis and precise treatment of head and neck tumors (Review).Molecular and clinical oncology · 2026Review
- The Gut-Skin Axis in Pediatric Atopic Dermatitis: Nutritional Modulation, Microbiome Interactions, and Emerging Precision Approaches.Nutrients · 2026Review
- Perspectives on the Limits and Clinical Alignment of Medical AI from Population Statistics to Individual Care.Bioengineering (Basel, Switzerland) · 2026Article
- Reframing Justice in Healthcare AI: An Ubuntu-Based Approach for Africa.Developing world bioethics · 2026Article
- Artificial intelligence and machine learning in heart and lung transplantation.EClinicalMedicine · 2026Review
- Applying Large Language Models in Perioperative Medicine With an Equity-Informed Perspective.Anesthesia and analgesia · 2026Article
- Developing and validating a sequence-aware deep learning model for infection risk prediction in home care.International journal of medical informatics · 2026Article
- Evaluating the Performance of LYDIA: An AI-Powered Assistant in the Detection of Metastatic Tumors to Optimize Clinical Workflows and Inform Soft Tissue Surgical Decision-Making.Bioengineering (Basel, Switzerland) · 2026Article
- PREFER-IT: A transdisciplinary co-created framework to realise inclusive health AI.PLOS digital health · 2026Article
- Review
- Agentic systems in computational pathology: architectures, evidence, and translational challenges.Journal of translational medicine · 2026Review
256 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
8 authors.
Funding
Abstract
In healthcare, the development and deployment of insufficiently fair systems of artificial intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models stratified across subpopulations have revealed inequalities in how patients are diagnosed, treated and billed. In this Perspective, we outline fairness in machine learning through the lens of healthcare, and discuss how algorithmic biases (in data acquisition, genetic variation and intra-observer labelling variability, in particular) arise in clinical workflows and the resulting healthcare disparities. We also review emerging technology for mitigating biases via disentanglement, federated learning and model explainability, and their role in the development of AI-based software as a medical device.
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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.