Methods, Modeling, and Findings

This unit investigates how large language models (LLMs) are studied and reported in health informatics research. Students learn research methods, modeling approaches, and how to interpret and communicate findings to inform ethical, evidence-based AI use in healthcare.

Learning Objectives

• Analyze the architecture, capabilities, and limitations of large language models as they relate to healthcare use cases using examples from the unit
• Apply appropriate research methods (study design, data collection, validation, and ethical safeguards) to plan a small-scale informatics study involving AI tools
• Demonstrate the construction and evaluation of a basic modeling workflow, including selection of metrics, validation techniques, and documentation of assumptions
• Evaluate findings from AI-driven studies by identifying significance, biases, limitations, and implications for patient care and downstream implementation