Artificial Intelligence-Derived Clinical Reports For Multidisciplinary Health Education: A Preliminary Approach

Abstract: Health education is a pivotal component in promoting overall well-being and preventing various diseases. With the rapid advancement of technology, particularly in the field of artificial intelligence (AI), health education is undergoing a transformation. This project aims at using artificial intelligence to generate clinical cases for multidisciplinary health students on a higher education institution. A large language model (LLM) known as OpenAI's ChatGPT (Generative Pretrained Transformer; OpenAI) is proposed to generate clinical case reports in several medical areas. For a more realistic insight about the reports, Fotor (an online platform for photo editing) was used to provide AI-generated images of each patient. By means of this AI tool, it is possible to generate clinical case reports containing the following information: patient’s main sociodemographic data, main complaint pathology (clinical diagnosis), history of previous illness etc. Further research aims at assessing quality and applicability of these data for health students.

Keywords: ChatGPT, artificial intelligence, health education, multidisciplinary approach

DOI: 10.54941/ahfe1004570

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