ReviewLancet regional health. Americas2026
AI literacy among healthcare professionals and students in the Americas.
Review in Lancet regional health. Americas, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Assessment of drug harm by final-year medical students and ChatGPT - a comparative analysis.Substance abuse treatment, prevention, and policy · 2026Article
- Between Awareness and Readiness: Perceptions of Artificial Intelligence Among Indonesian Mental Health Professionals.Behavioral sciences (Basel, Switzerland) · 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
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) applications in health care continue to grow exponentially, and AI-tools such as machine learning (ML), natural language processing (NLP), and generative pre-trained transformers (GPT) continue to transform medical education. The adoption of AI in medical education however remains geographically varied, with studies illustrating a relatively lower research output on medical AI literacy in Latin America (LATAM) countries compared to North America. AI-applications offer significant potential to broaden access to medical education and facilitate evidence-based support with clinical decision-making, particularly in low- and middle-income countries (LMICs). Enhancing AI literacy in such settings is of paramount importance - successful integration may alleviate historical disparities, while improper implementation may deepen regional inequities in medical education and health care. In this viewpoint article, we illustrate the current state of AI-based medical education across the Americas, highlight challenges in implementation, and offer collaborative, equitable, and regionally tailored strategies to enhance medical AI literacy among health care professionals and students.
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.