Artificial intelligence in medical education and the meaning of interaction with natural intelligence – an interdisciplinary approach
Open accessAbstract
Introduction: The practice of medicine is characterized by decision making in which digital techniques can provide good support. In this context, artificial intelligence (AI) is becoming increasingly important. The challenge for physicians, however, is to maintain an overview of the potential applications and usefulness of AI in order to be able to apply it efficiently and safely in their work. Therefore, appropriate skills must be imparted during the course of medical studies so that future practitioners can meet this requirement. Project description: The interdisciplinary research-related teaching and learning project “(Natural) Science and Technology in Medicine – NWTmed” brings together students at the Justus-Liebig-University Giessen (JLU) from the fields of medicine and other (natural) scientific disciplines in structured courses with the aim of thinking, learning, and working in an interdisciplinary and research-oriented manner already during their medical education. With the involvement of local researchers, a “multi-disciplinary” seminar on the basic premises, methods, and applications of AI was established. Results: The participants of the course came from a wide variety of fields of study, which promoted an interdisciplinary exchange and animated discussions. A gain in knowledge and an increase in interest in the topic of AI was noted in the evaluations, and a willingness on the part of the students to pursue further independent study was also expressed. Discussion and conclusion: The topic of AI and its relevance to the field of medicine is not yet sufficiently represented in medical education. It will require integration in the curriculum and performance evaluations as well as interdisciplinary and research-related teaching formats.
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Among the 6 articles with proposed changes to the medical curriculum, there was no evidence-based method backing those proposals.
“Similarly, among the 6 articles with proposed changes to medical curriculum, there was no evidence-based method backing these proposals.40,54”
From Educating Future Physicians in Artificial Intelligence (AI): An Integrative Review and Proposed Changes (2021) · cites this paper as [54]
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Digital Teaching and Digital Medicine: A national initiative is needed
Haag, M., Igel, C., Fischer, M. R., German Medical Education Society (GMA), C. &. &. T.-A. L. A. T., & Joint Working Group “Technology-Enhanced Teaching And Learning In Medicine (TeLL)” Of The German Association For Medical Informatics, B. A. E. (. A. T. G. I. S. (. (2018) · Europe PMC (PubMed Central) · doi:10.3205/zma001189 · Cited by 57 · see citing works
Brauchen wir einen Facharzt für Digitale Medizin?
Ertl, G. (2018) · DMW - Deutsche Medizinische Wochenschrift · doi:10.1055/a-0669-1618 · Cited by 7 · see citing works
Are estimations of radiomic image markers dispensable due to recent deep learning findings?
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Research works printed but not linked: 1
- [4]Lang J Repp H Die (Natur)Wissenschaft und Technik im Medizinstudium 2018 Jahrestagung der Gesellschaft für Medizinische Ausbildung (GMA). Wien, 19.-22.09.2018 Düsseldorf German Medical Science GMS Publishing House Doc11.1 10.3205/18gma050 · DOI
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Wood, E. A., Ange, B. L., & Miller, D. D. (2021) · Journal of Medical Education and Curricular Development · doi:10.1177/23821205211024078 · Cited by 261 · see citing works
Grunhut, J., Wyatt, A. T., & Marques, O. (2021) · Journal of Medical Education and Curricular Development · doi:10.1177/23821205211036836 · Cited by 161 · see citing works
“40,54 The detailed programs introduced in this study could be useful for medical educators in the development of curricula.”
BackgroundFranco D’Souza, R., Mathew, M., Mishra, V., & Surapaneni, K. M. (2024) · Medical Education Online · doi:10.1080/10872981.2024.2330250 · Cited by 147 · see citing works
Mapping the use of artificial intelligence in medical education: a scoping review
Rincón, E. H. H., Jimenez, D., Aguilar, L. A. C., Flórez, J. M. P., Tapia, Á. E. R., & Peñuela, C. L. J. (2025) · BMC Medical Education · doi:10.1186/s12909-025-07089-8 · Cited by 145 · see citing works
Moodi Ghalibaf, A., Moghadasin, M., Emadzadeh, A., & Mastour, H. (2023) · BMC Medical Education · doi:10.1186/s12909-023-04553-1 · Cited by 29 · see citing works
- Authors
- Lang, J., & Repp, H.
- Affiliations
- Justus-Liebig-Universität Gießen (DE)
- ORCID
- Repp, Holger
- Venue
- German Medical Science GMS Publishing House
- Publisher
- German Medical Science GMS Publishing House
- Published
- 2020-11-16
- Volume
- 37
- Issue
- 6
- Pages
- Doc59-Doc59
- PMC
- PMC7672386
- OpenAlex
- W3108873103
- Cited by
- 19
- References
- 4
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 5 · 2023: 2 · 2022: 3 · 2021: 3 · 2020: 1
- FWCI
- 0.66
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- German Medical Science (German Research Foundation) (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- GMS journal for medical education (cc-by)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Keywords
- artificial intelligence, medical education, human-AI interaction, curriculum integration, performance evaluation (human resources), interdisciplinary teaching, artificial intelligence in healthcare
- MeSH terms
- Artificial Intelligence, Curriculum, Education, Medical, Humans, Intelligence, Interdisciplinary Studies
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