APPLICATION OF AI IN TEACHING NUCLEAR MEDICINE AND RADIATION TECHNOLOGIES
DOI:
https://doi.org/10.47390/ydif-y2026v2i7/n09Keywords:
medical education, radiation oncology, artificial intelligence, MRI segmentation, ChatGPT in medicine, personnel training.Abstract
This article examines the transformation of medical education under the influence of generative artificial intelligence, which is literally reshaping training standards in radiation oncology. It also analyzes how large-scale language models and machine vision algorithms can not only relieve faculty of routine workloads but also provide young medical residents with access to a highly accurate clinical database in real time.
The article focuses on an experiment comparing human and machine skills: it compares the results of MRI image segmentation performed by experienced oncologists and a neural network. The obtained data (with a deviation of several cubic centimeters) confirm the high potential of AI for tumor localization, but simultaneously reveal the problem of "blind trust" in technology. Ultimately, the study substantiates the need to integrate digital literacy into curricula as a mandatory element of patient safety and the foundation for the development of modern high-tech medicine.
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