Program - TRACK C: Machine Learning in Real-World Drug Studies: Introduction to Prediction and Natural Language Processing (NLP) models

TRACK C: Machine Learning in Real-World Drug Studies: Introduction to Prediction and Natural Language Processing (NLP) models

Tracks

Track 3

Friday, October 30, 2026

9:00 - 10:30

PPS2

Details

This track introduces the foundational concepts and practical applications of machine learning (ML)-based prediction modeling, natural language processing (NLP), and large language models (LLMs) in pharmacoepidemiology and real-world data research. Through presentations and hands-on exercises, participants will learn (1) how LLM-based tools (e.g., codex, Claude code) can support day-to-day research workflow, (2) coding and machine learning-driven disease phenotyping strategies, and (3) critically evaluate epidemiologic biases and methodological challenges in ML-enhanced analyses. Track C is coordinated by Assistant Professor Yanmin Zhu and Dr. Richeek Pradhan.