ArticleJournal of medical education and curricular development
Medical Education: Considerations for a Successful Integration of Learning with and Learning about AI.
Article in Journal of medical education and curricular development. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Application of deep machine learning in dental education: a systematic review of effectiveness in dental students' teaching learning outcomes.Evidence-based dentistry · 2026Pooled it
- Content and structural needs assessment for an artificial intelligence education mobile app in healthcare: a mixed methods study.BMC medical education · 2025Pooled it
- [Medical education and artificial intelligence: perspectives and ethical challenges].Revista medica del Instituto Mexicano del Seguro Social · 2025Pooled it
- Validation of the Use of a Large Language Model for Detecting Sentiment in Student Course Evaluation.Family medicine · 2026Article
- Efficacy of Large Language Models in Providing Evidence-Based Patient Education for Celiac Disease: A Comparative Analysis.Nutrients · 2025Article
- Exploring the Challenges and Opportunities of ChatGPT in University Teaching for Health Sciences: A Narrative Review.Cureus · 2025Review
- Preparing Tomorrow's Physicians: The Case for Machine Learning in Medical Education.Journal of medical systems · 2025Article
- Large Language Models in Healthcare and Medical Applications: A Review.Bioengineering (Basel, Switzerland) · 2025Review
- Integrating artificial intelligence into medical curricula: perspectives of faculty and students in South Korea.Korean journal of medical education · 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) with its diverse domains such as expert systems and machine learning already has multiple potential applications in medicine. Based on the latest developments in the multifaceted field of AI, it will play a pivotal role in medicine, with a high transformative potential in multiple areas, including drug development, diagnostics, patient care and monitoring. In the pharmaceutical industry AI is also rapidly gaining a crucial role. The introduction of innovative medicines requires profound background knowledge and the latest means of communication. This drives us to intensively engage with the topic of medical education, which is becoming more and more demanding due to the dynamic knowledge landscape, among other things, accelerated even more by digitalization and AI. Therefore, we argue for the incorporation of AI-based tools and methods in medical education, including personalized learning, diagnostic pathways, and data analysis, to prepare healthcare professionals for the evolving landscape of AI in medicine and support the fluency in dealing with AI by regular contact with various AI-based tools (Learning with AI). Understanding AI's vast potential and its caveats as well as gaining a basic knowledge of how AI works should be an important part of medical education to ensure that physicians can effectively and responsibly leverage AI-based systems in their daily practice and in scientific communication (Learning about AI).
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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.