VCOM Louisiana Research Day Program Book 2024

Education, Simulation and Best Practices

Tiffani Najadifar, OMS-II; James Colquitt, PhD VCOM 64 AIRX: A, DOSE OF AI FOR SMART MEDICAL EDUCATION

Background: Artificial intelligence (AI) holds untapped potential for both medical education and healthcare. In response to the evolving landscape of AI, application platforms are emerging across academic and industrial sectors. Given the detailed nature of medical education practices, AI offers a unique opportunity for the field. This project aims to address the need for innovative and engaging teaching tools by leveraging the potential of AI generated content, with an early stage focus on the endocrine system. The goal is to provide medical students with the opportunity to analyze artificially-generated case studies. Utilizing artificial intelligence technologies can expedite the creation of realistic, curriculum-aligned simulation cases for utilization as pedagogical tools. This approach intends to engage students with course content in a practical learning exercise while allowing them to evaluate the accuracy of algorithmically-produced cases. Implementing artificial intelligence will dynamically scale next-generation educational content to match evolving curricula. Endocrine related pathologies offer an excellent feasibility study design as health issues that are based in endocrinology act as a catalyst for

ongoing chronic health concerns. With a global burden of diabetes and a progressively younger age of onset, medical students need higher fidelity training tools for endocrinology-related medical cases. Objective: The overarching objective of this research is to seamlessly integrate AI-generated cases into the medical curriculum, with a dedicated emphasis on endocrine related topics. The intention is not only to enhance the learning experience for medical students but also to provide a platform for critical analysis and evaluation of AI-generated medical scenarios. In addition, this project will leverage AI technologies to expedite the creation of realistic, endocrine focused and curriculum-aligned simulation cases for utilization as teaching tools. This project seeks to offer students a transformative educational experience, combining traditional medical education with the limitless possibilities of AI to foster deeper critical thinking and clinical reasoning skills. The envisioned platform serves as both a quality control mechanism, an interactive learning tool, and a feasibility study for utilizing AI generated cases across other medical practices. Ultimately, this project aims to better prepare student doctors to approach patient scenarios with more confidence and efficiency.

Methods: As the principal investigator, I will employ the Claude.AI system to automatically generate medical case studies pertaining to endocrinology. The Claude.AI system is an advanced AI platform specifically designed for medical case generation. An expert clinician will assist in comprehensively fact checking the AI-produced cases to identify requisite modifications to ensure medical accuracy and relevance to current instructional modules. Once expert validated, the case studies can undergo purposeful modification to align with programmatic goals. The collaboration will be multi-faceted, with the medical expert contributing clinical expertise and the student researcher offering a fresh perspective. The objective is to meticulously examine each case, identifying potential inaccuracies, clinical nuances, and curriculum alignment. Any necessary modifications will be documented and implemented to refine the AI generated cases. Moreover, the corrected case studies will not only serve as an opportunity for content validation but will also be strategically incorporated into the educational framework. These modified cases will function as interactive exercises, challenging students to critically

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