The University of Nevada, Reno School of Medicine (UNR Med) is incorporating artificial intelligence into its first-year curriculum through the Independent Data Exploration and Analysis (IDEA) Project, a required research course designed to strengthen students’ understanding of clinical research methods.
The IDEA Project was created by John Westhoff, M.D., MPH, associate professor and assistant dean of Student Research at UNR Med. The yearlong program aims to teach medical students how scientific evidence is generated, evaluated, and applied in clinical practice. Since its launch in 2023, the program has completed three cohorts.
Initially, students used general AI tools such as OpenAI’s ChatGPT and Anthropic’s Claude. The curriculum has since transitioned to TrialMind, a platform developed by Keiji AI specifically for research and clinical applications. UNR Med is the first medical school to integrate TrialMind directly into its coursework.
TrialMind supports literature reviews, trial design, and data analysis. The platform can identify, screen, and synthesize research studies, while also assisting students with coding, statistical modeling, and data extraction. Partner organizations associated with the platform include Mass General Brigham, Beth Israel Lahey Health, Regeneron Pharmaceuticals, and Guardant Health.
Faculty describe the platform as a research support tool rather than a shortcut. While it streamlines time-intensive tasks, students are still required to define research questions, determine relevant outcomes, and interpret findings. The program emphasizes analytical reasoning and study design over technical mastery of statistical software.
Each cohort is divided into 18 groups of four students, who work through structured milestones while developing independent case studies using real-world health data. The objective is to provide hands-on experience in evaluating methodology and understanding how research conclusions are formed.
Students participating in the IDEA Project have published research on topics including firearm-related mortality trends among U.S. youth, geographic patterns in cerebrovascular disease mortality, and opioid-related impacts on adults aged 65 and older. Some of these studies have been presented at national medical conferences and published in peer-reviewed journals.
Joseph Tran, an M.D./Ph.D. student who participated in the program, said the experience helped shape his professional development by demonstrating how clinically relevant research can emerge from well-defined questions and accessible methods. Tran, who holds a computer science degree from Stanford University, noted that large language models can reduce technical barriers, allowing researchers to focus on patient-centered outcomes and analysis.
Program leaders say the broader goal is to ensure that future physicians are equipped to critically evaluate scientific literature and apply evidence-based decision-making in practice. While not all students will pursue research careers, faculty emphasize that understanding study design and data interpretation remains essential to modern medical practice.
#SupplyChainNews #AIinHealthcare #MedicalEducation #HealthTech #DigitalInnovation
