USC Launches AI Biostatistics Course: When Large Language Models Meet Medical Research

The Keck School of Medicine at USC offers the PM599 course ("AI as a Tool for Biostatistics"), which systematically teaches biostatistics researchers to integrate large language models such as ChatGPT, Claude, and Gemini into their research workflows. It covers prompt engineering, ethical guidelines, and hands-on AI-assisted programming in R, aiming to improve research efficiency and standardize the use of AI tools.

The development of generative AI technology is driving changes in the fields of medicine and biostatistics. Traditional statistical methods have limited efficiency in handling massive data, complex designs, and interdisciplinary collaboration. Biostatistics researchers often face time-consuming tasks such as processing complex R code and writing papers. LLMs offer the possibility to improve efficiency, but issues like proper usage and ethical risk avoidance need urgent resolution. This course was thus created to fill the knowledge gap.

The course adopts a dual-module design of "Theory + Experiment". The theoretical part includes five sections: Course Overview (AI as a tool, not a replacement; emphasizing responsibility and critical thinking), LLM Panorama (principles, characteristics of mainstream models, and applicable scenarios), AI Applications in Biostatistics (cases like data cleaning, hypothesis generation, paper writing), Ethical Guidelines (journal policies, fund disclosure requirements), and Hands-on Prompt Engineering (RCTF framework and iterative optimization). The experimental section is divided into four phases: platform preparation, multi-LLM comparison, prompt optimization, and hands-on AI-assisted programming in R.

Course tools include ChatGPT (USC-authorized version), Claude.ai, Gemini, RStudio, etc., with advanced tools like Antigravity and Cursor. Assignments require students to select at least two AI tools for comparative testing in biostatistics scenarios, optimize prompt strategies, and write critical reflections. Submissions are made via Brightspace to cultivate technical mastery and metacognitive skills.

The PM599 course marks the shift of AI education from an elective to a required course, and from technical experimentation to systematic training. The course adheres to the principles of practical orientation, ethics first, tool neutrality, and continuous iteration. It provides an example for the biostatistics field to embrace technological change while maintaining rigor, and has reference value for the domestic medical statistics community.

Generative AI is reshaping the form of medical research, and the PM599 course reflects the academic community's rational response. Researchers need to master the use of AI tools and understand their boundaries—AI is an assistant, but the soul of research lies in human professional judgment and academic integrity. Domestic institutions can learn from this course paradigm to develop localized AI biostatistics courses and cultivate interdisciplinary talents.