ArticleNature communications2024
Generalizability assessment of AI models across hospitals in a low-middle and high income country.
Article in Nature communications, 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 59 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.
Prediction of Infectious Diseases in LMICs Using Electronic Health Record Data
Who cites it
59 citing papers in PubMed, 1 synthesis or guideline pooled it.
- AI for IMPACTS Framework for Evaluating the Long-Term Real-World Impacts of AI-Powered Clinician Tools: Systematic Review and Narrative Synthesis.Journal of medical Internet research · 2025Pooled it
- An eyecare foundation model for clinical assistance: a randomized controlled trial.Nature medicine · 2025Trial
- Artificial intelligence readiness in Pakistan's medical and dental education: training-phase decline, a knowledge-practice paradox, and the role of digital determinants of health.Medical education online · 2026Article
- Is Digital Healthcare Better Than None? The Digital Health Technology Dilemma in Low-Income Countries.Asian bioethics review · 2026Article
- Navigating Healthcare AI Governance: the Comprehensive Algorithmic Oversight and Stewardship Framework for Risk and Equity.Health care analysis : HCA : journal of health philosophy and policy · 2026Article
- Artificial Intelligence for Improving the Management of People With Epilepsy in Low-and-Middle Income Countries.European journal of neurology · 2026Review
- Current research landscape and future prospects of in silico modeling approaches for atopic dermatitis.JID innovations : skin science from molecules to population health · 2026Review
- Diagnostic accuracy of deep learning-assisted low-dose CT screening for lung cancer detection: a systematic review and meta-analysis.Diagnostic and prognostic research · 2026Article
- Development and Deployment of DeepSeek-Based Applications in Healthcare: A Chinese Perspective.Health care science · 2026Article
- Handling missing data: AI approach for survival prediction in lung cancer despite missing data.NPJ digital medicine · 2026Article
- AI-Assisted Chest X-Ray Interpretation in Resource-Limited Settings: LuAna Stepped-Wedge Trial Protocol.JMIR research protocols · 2026Article
- Generalization of AI-Based Gestational Age Assessment Using Blind Sweep Ultrasonography.JAMA network open · 2026Article
- Artificial intelligence in surgical care within low-income and middle-income countries: a scoping review of development, validation, and deployment.EClinicalMedicine · 2026Review
- Data reuse in global health: perspectives from actors in policy, funding and research.BMJ global health · 2026Article
- Characterizing patients who benefit from mature medical AI models in real-world clinical applications.PLOS digital health · 2026Article
- The role of artificial intelligence in advancing urologic care: From diagnostics to therapeutics.Surgery in practice and science · 2026Review
- Embracing the Digital Revolution: How Artificial Intelligence is Transforming Clinical Trials in Older Participants.Drugs & aging · 2026Review
- Artificial intelligence in cardiology: a narrative review with focus on patient outcomes.Cardiovascular diagnosis and therapy · 2026Review
- The cyber-physical paradigm for lifetime aortic valve management: a synthesis of robotics, artificial intelligence, and augmented reality.Journal of robotic surgery · 2026Review
- Applying biotechnology to overcome cancer drug resistance and improve public health outcomes.Osong public health and research perspectives · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
The integration of artificial intelligence (AI) into healthcare systems within low-middle income countries (LMICs) has emerged as a central focus for various initiatives aiming to improve healthcare access and delivery quality. In contrast to high-income countries (HICs), which often possess the resources and infrastructure to adopt innovative healthcare technologies, LMICs confront resource limitations such as insufficient funding, outdated infrastructure, limited digital data, and a shortage of technical expertise. Consequently, many algorithms initially trained on data from non-LMIC settings are now being employed in LMIC contexts. However, the effectiveness of these systems in LMICs can be compromised when the unique local contexts and requirements are not adequately considered. In this study, we evaluate the feasibility of utilizing models developed in the United Kingdom (a HIC) within hospitals in Vietnam (a LMIC). Consequently, we present and discuss practical methodologies aimed at improving model performance, emphasizing the critical importance of tailoring solutions to the distinct healthcare systems found in LMICs. Our findings emphasize the necessity for collaborative initiatives and solutions that are sensitive to the local context in order to effectively tackle the healthcare challenges that are unique to these regions.
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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.