ArticleJMIR medical education2023
Data Science as a Core Competency in Undergraduate Medical Education in the Age of Artificial Intelligence in Health Care.
Article in JMIR medical education, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 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
28 citing papers in PubMed, 2 syntheses or guidelines pooled it, 44 citations in OpenAlex.
- Development of AI competencies within the medical curriculum.Frontiers in medicine · 2026Pooled it
- Global trends of big data analytics in health research: a bibliometric study.Frontiers in medicine · 2025Pooled it
- Addressing Clinician-Educator Hesitancy Toward Artificial Intelligence Through a Peer-Led Instructional Design.Cureus · 2026Article
- Bridging the Implementation Gap in Medical AI Education: 3-Lever Framework for Concurrent Reform.JMIR medical education · 2026Article
- Artificial Intelligence in Public Health Education: A Scoping Review of Workforce Competency Development.Health science reports · 2026Article
- Dental students' knowledge, perceptions, and educational needs regarding artificial intelligence: a multinational cross-sectional survey.BMC medical education · 2026Article
- A strategic framework for data science integration in undergraduate medical education and clinical training.Journal of education and health promotion · 2026Review
- Design and application of a web-based intelligent ophthalmic image analysis teaching platform.Frontiers in medicine · 2026Article
- Twelve tips for developing and implementing AI curriculum for undergraduate medical education.Medical education online · 2025Review
- Artificial intelligence in undergraduate medical education: an updated scoping review.BMC medical education · 2025Article
- Institutionalizing convergence education for medical artificial intelligence.Biomedical engineering letters · 2025Review
- Artificial intelligence in medical education for pulmonary nodule management: a narrative review.Translational lung cancer research · 2025Review
- Refining AI perspectives: assessing the impact of ai curricular on medical students' attitudes towards artificial intelligence.BMC medical education · 2025Article
- Interdisciplinary medical education practices: building a case-driven interdisciplinary simulation system based on public datasets.BMC medical education · 2025Article
- Fine-tuning of language models for automated structuring of medical exam reports to improve patient screening and analysis.Scientific reports · 2025Article
- Novel Blended Learning on Artificial Intelligence for Medical Students: Qualitative Interview Study.JMIR medical education · 2025Article
- Leveraging Datathons to Teach AI in Undergraduate Medical Education: Case Study.JMIR medical education · 2025Article
- Engaging Stakeholders Using the Competency Matrix Model: A Framework for Current and Future Health Informaticists.Applied clinical informatics · 2025Article
- Exploring the role of moxibustion robots in teaching: a cross-sectional study.BMC medical education · 2025Article
- Adapting data science competencies by role and purpose: Voice AI.Frontiers in digital health · 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
7 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The increasingly sophisticated and rapidly evolving application of artificial intelligence in medicine is transforming how health care is delivered, highlighting a need for current and future physicians to develop basic competency in the data science that underlies this topic. Medical educators must consider how to incorporate central concepts in data science into their core curricula to train physicians of the future. Similar to how the advent of diagnostic imaging required the physician to understand, interpret, and explain the relevant results to patients, physicians of the future should be able to explain to patients the benefits and limitations of management plans guided by artificial intelligence. We outline major content domains and associated learning outcomes in data science applicable to medical student curricula, suggest ways to incorporate these themes into existing curricula, and note potential implementation barriers and solutions to optimize the integration of this content.
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.