ReviewCell reports. Medicine2023
Artificial intelligence education: An evidence-based medicine approach for consumers, translators, and developers.
Review in Cell reports. Medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 3 of them syntheses 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
47 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- [Medical education and artificial intelligence: perspectives and ethical challenges].Revista medica del Instituto Mexicano del Seguro Social · 2025Pooled it
- Reporting guideline for Chatbot Health Advice studies: the CHART statement.BMC medicine · 2025Guideline
- A systematic review of the impact of artificial intelligence on educational outcomes in health professions education.BMC medical education · 2025Pooled it
- Measuring AI literacy in medical students: scale development and validation within a self-determination theory framework.Medical education online · 2026Article
- AI In Leukemia Diagnostics: Complementing the Pathologist's Role.International journal of laboratory hematology · 2026Review
- Role-Differentiated AI Competencies and Curriculum Implications for Health Professions Education: Qualitative Study.JMIR medical education · 2026Article
- Empowering Educators to Build AI Chatbots in Health Professions Education: Tutorial on a No-Code Design Workflow.JMIR medical education · 2026Article
- Artificial Intelligence Competencies and Educational Needs Among ERNICA Members: Results of a Multinational Survey.European journal of pediatric surgery : official journal of Austrian Association of Pediatric Surgery ... [et al] = Zeitschrift fur Kinderchirurgie · 2026Article
- AI literacy among healthcare professionals and students in the Americas.Lancet regional health. Americas · 2026Review
- Artificial intelligence needs better health systems to reduce inequalities.NPJ digital medicine · 2026Review
- Clinical artificial intelligence applications of vision-language foundation models.PLOS digital health · 2026Review
- Defining the artificial intelligence knowledge gap in surgery: experience and perspectives from surgical resident and postgraduate.Updates in surgery · 2026Article
- What the AI era doctor should know: a scoping review of proposed artificial intelligence competencies for medical education.NPJ digital medicine · 2026Article
- Reimagining pharmacology education.Pharmacological reviews · 2026Review
- Questionnaires on Perceptions of Artificial Intelligence in Health Care Among Health Care Students: Cross-Cultural Translation Into French and Linguistic Validation.JMIR medical education · 2026Article
- Development and validation of a competency-based evaluation framework for clinical medical trainees in the era of artificial intelligence: a mixed-methods study in China.BMC medical education · 2026Article
- On AI's role in training professionals in assisted reproductive technology.Frontiers in artificial intelligence · 2026Article
- Large Language model (LLM) in temporomandibular disorder education: a comparative study.BMC oral health · 2025Article
- Advancing AI literacy in Canadian orthopedic education: a framework for equitable and inclusive training.Canadian medical education journal · 2025Article
- Digital health competences and AI beliefs as conditions for the practice of evidence-based medicine: a study of prospective physicians in Canada.Medical education online · 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
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Current and future healthcare professionals are generally not trained to cope with the proliferation of artificial intelligence (AI) technology in healthcare. To design a curriculum that caters to variable baseline knowledge and skills, clinicians may be conceptualized as "consumers", "translators", or "developers". The changes required of medical education because of AI innovation are linked to those brought about by evidence-based medicine (EBM). We outline a core curriculum for AI education of future consumers, translators, and developers, emphasizing the links between AI and EBM, with suggestions for how teaching may be integrated into existing curricula. We consider the key barriers to implementation of AI in the medical curriculum: time, resources, variable interest, and knowledge retention. By improving AI literacy rates and fostering a translator- and developer-enriched workforce, innovation may be accelerated for the benefit of patients and practitioners.
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.