Evidence map›Paper›PMID 42582818›Full record

ArticleJournal of medical education and curricular development

An Interactive, Project-Based AI in Healthcare Curriculum for Clinicians and Medical Educators.

Hiba Hamdar

Abstract read
In one paragraph

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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Hiba HamdarMedical Learning Skills Academy, Beirut, Lebanon.ORCID https://orcid.org/0000-0002-4488-7323

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: A persistent skills gap separates the rapid development of artificial intelligence (AI) tools in medicine from clinicians' ability to critically evaluate, adopt, and govern them. Existing AI-in-healthcare education is typically delivered through passive, lecture-based formats that do not require learners to apply frameworks to real clinical or institutional problems. Methods: We designed and piloted a 10-week, interactive AI in Healthcare curriculum using a Socratic teaching method: each concept is taught, followed by a targeted question the learner must answer before advancing; every task submission receives detailed individualized correction. The curriculum requires each learner to develop an original AI project addressing a real clinical or educational problem, culminating in a published GitHub repository documenting a structured readiness-objectives-adoption-data (R.O.A.D.) analysis, algorithm selection, an ethics and governance framework, and a validation plan. Results: Pilot delivery of the curriculum's foundational module demonstrated feasibility of the interactive correction model, with measurable improvement across four graded learner tasks, including increased precision in formulating measurable, evidence-based project objectives following targeted instructor correction. Discussion: This curriculum offers a generalizable, no-cost model for closing the AI evaluation skills gap in healthcare education, combining interactive correction with a mandatory, learner-defined capstone project. We discuss plans for formal assessment validation and full-cohort implementation.

Indexed as

active learningAI literacyartificial intelligenceclinical decision supportcontinuing medical educationcurriculum developmentinterprofessional educationmachine learning

Identifiers

PMID42582818
PMCPMC13458112

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

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.