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Artificial Intelligence in Health AI in higher medical education

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Figure 2. Geographical distribution of papers related to artificial intelligence (AI) in medical (med) education (ed) and ethics (ethics) based on the Web
of Science. (A) Distribution of papers on AI+med+ed. (B) Distribution of papers on AI+med+ed+ethics.

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Figure 3. Geographical distribution of papers related to artificial intelligence (AI) in medical (med) education (ed) and XR based on the Web of Science.
(A) Distribution of papers on AI+med in radiology. (B) Distribution of papers on AI+med in Extended Reality (i.e., virtual reality, augmented reality,
mixed reality, and metaverse).

tool. Similarly, Andersson et al. and Mosh et al. concluded August 2023, Gordon et al. conducted a thorough search
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that AI helps reduce physicians’ workload. In addition, of publications found in PubMed/MEDLINE, EMBASE,
during the COVID-19 pandemic, distance learning and MedEdPublish, looking for keywords connected to the
developed significantly and came to cover the whole world, use of AI in medical education. The largest preponderance
not just people living in remote and inaccessible areas. occurred in the field of radiology (11.2%), followed by
This was made possible by the development of technology, surgery (8.7%). Then, Pinto dos Santos et al. conducted
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including AI-based solutions. Furthermore, the high an anonymous survey concerning the attitude of radiology
cost of practical offline classes, especially in the field of students to AI applications, whereby 83% of participants
medicine, and the consequently limited opportunities for believed AI-based algorithms could potentially detect
participation make remote learning solutions appear to be pathological changes in radiological images, while 56%
an accessible and natural development of the educational felt they were unable to correctly interpret these changes.
sector. Indeed, the potential of AI in distance education At the same time, 68% of respondents admitted they were
has been demonstrated by Garlinska et al., who pointed not aware of the technologies and risks associated with AI
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out that AI-based algorithms can be applied to the implementation in radiology. This indicates a significant
personalization of learning content, automated grading, gap among medical staff regarding AI technology, which
and virtual touring, including as they do features such as may hinder its effective use.
speech-to-text and text-to-speech. Visualization constitutes a major area where AI-based
More specifically, AI has the potential to improve the solutions play a significant role in medical education. These
diagnostic process, which is crucial for education in this solutions enable the creation of realistic 3D visualizations
field. Radiology is a significant area of medicine. In July and of organs, their abnormalities, and the entire human
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Volume 2 Issue 1 (2025) 4 doi: 10.36922/aih.3276