ArticleAcademic medicine : journal of the Association of American Medical Colleges2019
Computing for Medicine: Can We Prepare Medical Students for the Future?
Article in Academic medicine : journal of the Association of American Medical Colleges, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.
- Pooled it
- OpenSpineConsortium: An Open-Source Framework for Medical Student Engagement in Computational Spine Imaging Research.Cureus · 2026Article
- Twelve tips for developing and implementing AI curriculum for undergraduate medical education.Medical education online · 2025Review
- Preparing healthcare leaders of the digital age with an integrative artificial intelligence curriculum: a pilot study.Medical education online · 2024Article
- Understanding and training for the impact of large language models and artificial intelligence in healthcare practice: a narrative review.BMC medical education · 2024Review
- Artificial intelligence education: An evidence-based medicine approach for consumers, translators, and developers.Cell reports. Medicine · 2023Review
- Introducing medical students to deep learning through image labelling: a new approach to meet calls for greater artificial intelligence fluency among medical trainees.Canadian medical education journal · 2023Article
- Perceptions of US Medical Students on Artificial Intelligence in Medicine: Mixed Methods Survey Study.JMIR medical education · 2022Article
- Technology Literacy in Undergraduate Medical Education: Review and Survey of the US Medical School Innovation and Technology Programs.JMIR medical education · 2022Article
- Medical Data Mining Course Development in Postgraduate Medical Education: Web-Based Survey and Case Study.JMIR medical education · 2021Article
- Digital Health Training Programs for Medical Students: Scoping Review.JMIR medical education · 2021Article
- Medical Student Training in eHealth: Scoping Review.JMIR medical education · 2020Article
- What do medical students actually need to know about artificial intelligence?NPJ digital medicine · 2020Article
- Computer Programming: Should Medical Students Be Learning It?JMIR medical education · 2019Article
- Developing and validating an accelerated online Canadian training in data science for the health sciences community.Digital healthArticle
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 at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
problemTechnology can transform health care; future physicians need to keep pace to ensure optimal patient care. Because future doctors are poorly prepared in computer literacy, the authors designed a computer programming certificate course. This Innovation Report describes the course and findings from a qualitative study to understand the ways it prepares medical students to use computing science and technology in medicine. APPROACH: The 14-month Computing for Medicine certificate course (C4M, offered beginning in February 2016), University of Toronto, is comprised of hands-on workshops to introduce programming accompanied by homework exercises, seminars by computer science experts on the application of programming to medicine, and coding projects. Using purposive and maximal variation sampling, 17 students who completed the course were interviewed from April-May 2017. Thematic analysis was performed using an iterative constant comparison approach. OUTCOMES: Participants praised the C4M as an opportunity to achieve computer literacy-including language, syntax, and fundamental computational ideas (and their application to medicine)-and acquire or strengthen algorithmic and logical thinking skills for approaching problems. They highlighted that the course illustrated linkages between computer science and medicine. Participants acknowledged a sometimes-existent chasm between producers and users of technology in medicine, recommending two-way communication between the disciplines when developing technology for use in medicine. NEXT STEPS: We recommend that medical schools consider computer literacy an essential skill to foster future collaborative computing partnerships for improved technology use by physicians and optimal patient care. We encourage further evaluation of future iterations of the C4M and similar courses.
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.