Unlocking the Potential of ChatGPT in Medical Education and Practice (Preprint)

Abstract

<sec> <title>BACKGROUND</title> ChatGPT is an innovative application of advanced artificial intelligence technology in the field of medical education and practice. This technology leverages the capabilities of large language models, such as OpenAI's GPT-3, to provide users with natural language processing and generation capabilities. In the context of medical education and practice, ChatGPT can be used to enhance learning and decision-making by providing students, healthcare providers, and patients with access to instant, accurate information and guidance. With its ability to understand and respond to complex medical inquiries, ChatGPT has the potential to revolutionize the way medical knowledge is acquired and applied, making medical education and care more efficient and effective. By integrating this technology into medical education and practice, healthcare professionals can stay up-to-date with the latest developments, improve patient outcomes, and drive innovation in the field. </sec> <sec> <title>OBJECTIVE</title> The objective of this study is to examine the student's views regarding the utilization of ChatGPT for educational purposes in the United Arab Emirates. </sec> <sec> <title>METHODS</title> The theoretical framework involves the adoption properties, including the trialability, observability, compatibility, users’ satisfaction, personal innovativeness, and Technology Acceptance Model (TAM) constructs. The uniqueness of this paper lies in its theoretical model which connects both individual-based characteristics and technology-based aspects. The originality of the study lies in its theoretical framework which combines both individual-based characteristics and technological features. Furthermore, a unique hybrid analysis method will be applied, combining deep learning-based structural equation modeling (SEM) and artificial neural network (ANN) analysis. Additionally, the study employs the Importance-Performance Map Analysis (IPMA) to assess the impact and performance of the various factors. </sec> <sec> <title>RESULTS</title> The results of the ANN and IPMA analysis indicated that Perceived Usefulness (PU) is a critical predictor of Users' Intention to Use the ChatGPT. </sec> <sec> <title>CONCLUSIONS</title> This finding is significant as it helps decision-makers in the educational sector to prioritize their efforts and plans based on the relative significance of each factor. The study also has important methodological implications, demonstrating the potential of deep artificial neural network (ANN) architecture to provide a deeper understanding of the complex relationships among the factors in a theoretical model. </sec> <sec> <title>CLINICALTRIAL</title> n/a </sec>

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