ArticleScientific reports2024
Mitigating machine learning bias between high income and low-middle income countries for enhanced model fairness and generalizability.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07432061 (Prediction of Infectious Diseases in LMICs Using Electronic Health Record Data), which is not on this map. Cited by 18 papers, 1 of them a synthesis that pooled it.
What it found
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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.
Prediction of Infectious Diseases in LMICs Using Electronic Health Record Data
Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Exploring an AI-driven dynamic triage system for real-time patient risk reassessment in emergency departments in low-resource settings.Frontiers in digital health · 2026Pooled it
- Harnessing Artificial Intelligence in Health Research in Low-Income and Middle-Income Countries: Potential and Caution.Mayo Clinic proceedings. Digital health · 2026Review
- Bias Mitigation Across the Healthcare Artificial Intelligence Lifecycle: A Structured Narrative Review.Cureus · 2026Review
- From Data Poverty to Data Sovereignty: Operationalizing Gold-Standard Biomedical Datasets in Low- and Middle-Income Countries.JMIR medical informatics · 2026Article
- Bridging the mentorship divide: how large language models could reshape medical workforce equity.NPJ digital medicine · 2026Article
- Artificial intelligence in prediabetes care: applications in screening, risk prediction, and lifestyle intervention.Frontiers in endocrinology · 2026Review
- Connecting biospecimens and data: a scoping review-informed conceptual framework for digital infrastructure in biobanking and genomic research in low- and middle-income countries.Frontiers in public health · 2026Article
- Translational Potential and Explainability of Artificial Intelligence-Based Clinical Decision Support for Adults in Intensive Care: A Scoping Review.Journal of multidisciplinary healthcare · 2026Review
- AI without representation is just inequity at scale: on the exportation of unrepresentative artificial intelligence models to the Global South.Frontiers in artificial intelligence · 2026Article
- Safety of a large language model-based clinical decision support system in African primary healthcare.Nature health · 2026Article
- The role of machine learning in autism spectrum disorder assessment and management.Pediatric research · 2025Review
- Global Cancer Imaging Access: Addressing Barriers and Harnessing Innovations.Radiology. Imaging cancer · 2025Review
- Validation of the American Heart Association Predicting Risk of Cardiovascular Disease Events Equations in Diverse Socioeconomic Groups: The All of Us Cohort.Journal of the American Heart Association · 2025Article
- The application of machine learning models in a resource-constrained environment.Irish journal of medical science · 2025Article
- The Transformative Role of Artificial Intelligence in Dentistry: A Comprehensive Overview Part 2: The Promise and Perils, and the International Dental Federation Communique.International dental journal · 2025Review
- AI-Driven Advances in Low-Dose Imaging and Enhancement-A Review.Diagnostics (Basel, Switzerland) · 2025Review
- AI-Y: An AI Checklist for Population Ethics Across the Global Context.Current epidemiology reports · 2025Review
- Generalizability assessment of AI models across hospitals in a low-middle and high income country.Nature communications · 2024Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Collaborative efforts in artificial intelligence (AI) are increasingly common between high-income countries (HICs) and low- to middle-income countries (LMICs). Given the resource limitations often encountered by LMICs, collaboration becomes crucial for pooling resources, expertise, and knowledge. Despite the apparent advantages, ensuring the fairness and equity of these collaborative models is essential, especially considering the distinct differences between LMIC and HIC hospitals. In this study, we show that collaborative AI approaches can lead to divergent performance outcomes across HIC and LMIC settings, particularly in the presence of data imbalances. Through a real-world COVID-19 screening case study, we demonstrate that implementing algorithmic-level bias mitigation methods significantly improves outcome fairness between HIC and LMIC sites while maintaining high diagnostic sensitivity. We compare our results against previous benchmarks, utilizing datasets from four independent United Kingdom Hospitals and one Vietnamese hospital, representing HIC and LMIC settings, respectively.
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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.