ReviewDigital health
Can artificial intelligence revolutionize healthcare in the Global South? A scoping review of opportunities and challenges.
Review in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 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
- Comparative evaluation of handwriting recognition by large language models (LLMs) in interpreting handwritten medication lists.Exploratory research in clinical and social pharmacy · 2026Article
- Nationwide implementation of AI-assisted telemedicine in El Salvador.Lancet regional health. Americas · 2026Article
- AI-driven nanomedicine for cancer theranostics.Molecular cancer · 2026Review
- Beyond the hype: navigating the real-world applications of artificial intelligence (AI) in healthcare.Medical review (2021) · 2026Review
- Mapping Biomedical Engineering Education and Research in Sub-Saharan Africa: A Bibliometric and Systematic Analysis.Advances in medical education and practice · 2026Review
- The AI Health Arms Race: A Critical Perspective on Big Tech and the Widening Global Health Equity Gap.Journal of multidisciplinary healthcare · 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI) health applications developed in Global North countries are being diffused to the Global South but not without problems. Objective: The goal of this integrative scoping review was to identify recent studies from 2022 to 2025 describing the contributions and challenges in using AI health applications in the Global South. Methods: An integrative scoping review of 24 studies from seven databases identified four themes. Major Findings: This review adds to previous investigations by 1) focusing on data interoperability to resolve gaps in digitizing global health data required for accurate machine learning, 2) examining formidable economic and infrastructure hurdles for adoption and implementation of health AI in low-resource countries, 3) identifying barriers faced by emerging economies for partnerships with global AI biotech companies in AI health startups, and 4) calling for regulations and global surveillance of AI health applications. Conclusions: Practical implications for the future use of AI health applications in the Global South are discussed concluding that applications developed and trained on datasets from high income countries need to be recalibrated to work in the Global South. Additionally, due to the health-related disparities within the Global North the adoption of AI needs to be considered in its own context.
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.