ReviewAnnual review of biomedical data science2023
Addressing the Challenge of Biomedical Data Inequality: An Artificial Intelligence Perspective.
Review in Annual review of biomedical data science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 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
28 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence in Cardiovascular Medicine: Focus on Hypertension.Hypertension (Dallas, Tex. : 1979) · 2026Pooled it
- Graph Neural Networks in Neuroimaging: Current Status and Biostatistical Considerations for Clinical Deployment.Annals of biomedical engineering · 2026Review
- Bridging ancestry gaps in genomic risk prediction with tabular foundation models.Bioinformatics (Oxford, England) · 2026Article
- Equitable Health Intelligence: An Open Benchmark of Multi-Population Machine Learning for Omics-Based Cancer Prognosis.bioRxiv : the preprint server for biology · 2026Article
- Bridging Ancestry Gaps in Genomic Risk Prediction with Tabular Foundation Models.bioRxiv : the preprint server for biology · 2026Article
- Omics-based Cancer Prognosis Across Ethnic Groups: From Feature Engineering to Disparity Detection and Mitigation.IEEE transactions on artificial intelligence · 2026Article
- Data Representation Bias and Conditional Distribution Shift Drive Predictive Performance Disparities in Multi-Population Machine Learning.bioRxiv : the preprint server for biology · 2026Article
- AI and network biology for rational polypharmacology in signaling drug design: a review.NPJ precision oncology · 2026Review
- Advancing data science research education in Africa through datathon-driven innovations.Scientific reports · 2026Article
- Integration of fairness-awareness into clinical language processing models.Communications medicine · 2026Article
- Temporal network analysis in systems biology: concepts, inference, and validation.Frontiers in bioinformatics · 2026Review
- MOTLAB: A Weighted Multi-Omics Transfer Learning Approach to Mitigate Breast Cancer Racial Disparities.bioRxiv : the preprint server for biology · 2025Article
- The Genetic Data Market: Institutional Governance of Academic/Industry Research Partnerships for the Public Good.The American journal of bioethics : AJOB · 2025Article
- Artificial Intelligence Driven Innovation: Advancing Mesenchymal Stem Cell Therapies and Intelligent Biomaterials for Regenerative Medicine.Bioengineering (Basel, Switzerland) · 2025Review
- Artificial Intelligence and Multi-Omics in Pharmacogenomics: A New Era of Precision Medicine.Mayo Clinic proceedings. Digital health · 2025Review
- Artificial Intelligence in Personalized Medicine for Diabetes Mellitus: A Narrative Review.Cureus · 2025Review
- Lost in .*VCF Translation. From Data Fragmentation to Precision Genomics: Technical, Ethical, and Interpretive Challenges in the Post-Sequencing Era.Journal of personalized medicine · 2025Review
- How multi-scale modeling can help examine social determinants of health and resulting disparities.PLoS computational biology · 2025Article
- Digital pathways connecting social and biological factors to health outcomes and equity.NPJ digital medicine · 2025Article
- Global Research Landscape of Artificial Intelligence in Urology: A Systematic Analysis of Emerging Trends, Clinical Impact, and Collaborative Networks (1971-2024).Medical journal of the Islamic Republic of Iran · 2025Article
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
Artificial intelligence (AI) and other data-driven technologies hold great promise to transform healthcare and confer the predictive power essential to precision medicine. However, the existing biomedical data, which are a vital resource and foundation for developing medical AI models, do not reflect the diversity of the human population. The low representation in biomedical data has become a significant health risk for non-European populations, and the growing application of AI opens a new pathway for this health risk to manifest and amplify. Here we review the current status of biomedical data inequality and present a conceptual framework for understanding its impacts on machine learning. We also discuss the recent advances in algorithmic interventions for mitigating health disparities arising from biomedical data inequality. Finally, we briefly discuss the newly identified disparity in data quality among ethnic groups and its potential impacts on machine learning.
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.