ArticleMedical education online2024
Preparing healthcare leaders of the digital age with an integrative artificial intelligence curriculum: a pilot study.
Article in Medical education online, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Accuracy of Large Language Models When Answering Clinical Research Questions: Systematic Review and Network Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Integrating Large Language Models Into Trauma Education for Medical Students: Randomized Controlled Pilot Trial.JMIR medical education · 2026Trial
- Workflow-embedded AI as a cognitive scaffold: A randomized trial on knowledge retention and diagnostic competency in undergraduate radiology education.European journal of radiology open · 2026Article
- Current Landscape of Curriculum Development and Implementation in Medical Artificial Intelligence: A Scoping Review.Journal of multidisciplinary healthcare · 2026Review
- Twelve tips for developing and implementing AI curriculum for undergraduate medical education.Medical education online · 2025Review
- Generative AI as the First Patient: Practice, Feedback, and Confidence.Medical science educator · 2025Article
- Refining AI perspectives: assessing the impact of ai curricular on medical students' attitudes towards artificial intelligence.BMC medical education · 2025Article
- Adaptive consensus optimization in blockchain using reinforcement learning and validation in adversarial environments.Frontiers in artificial intelligence · 2025Article
- Perceptions and attitudes of health science students relating to artificial intelligence (AI): A scoping review.Health science reports · 2024Article
- Optimization of diagnosis and treatment of hematological diseases via artificial intelligence.Frontiers in medicine · 2024Review
- AI's pivotal impact on redefining stakeholder roles and their interactions in medical education and health care.Frontiers in digital health · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is rapidly being introduced into the clinical workflow of many specialties. Despite the need to train physicians who understand the utility and implications of AI and mitigate a growing skills gap, no established consensus exists on how to best introduce AI concepts to medical students during preclinical training. This study examined the effectiveness of a pilot Digital Health Scholars (DHS) non-credit enrichment elective that paralleled the Dartmouth Geisel School of Medicine's first-year preclinical curriculum with a focus on introducing AI algorithms and their applications in the concurrently occurring systems-blocks. From September 2022 to March 2023, ten self-selected first-year students enrolled in the elective curriculum run in parallel with four existing curricular blocks (Immunology, Hematology, Cardiology, and Pulmonology). Each DHS block consisted of a journal club, a live-coding demonstration, and an integration session led by a researcher in that field. Students' confidence in explaining the content objectives (high-level knowledge, implications, and limitations of AI) was measured before and after each block and compared using Mann-Whitney
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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.