This project aims to design an integrated, AI enabled framework that supports clinicians in the area of patient care:

1. Early risk identification and staging of chronic conditions (e.g., kidney and cardiovascular diseases, hepatitis, and other longterm conditions), and/or

2. Individualized therapy management for treatments—especially those with narrow therapeutic ranges—by informing safe and effective dosing and ongoing monitoring.

By unifying predictive analytics with longitudinal treatment guidance, the project seeks to improve patient outcomes while supporting clinical decision making in real world settings.

Student will contribute to one or more phases of the project according to interest and preparation. Responsibilities may include data preparation, feature representation, modeling experiments, evaluation, documentation, and results communication. Specific assignments will be scoped collaboratively and may evolve as the project progresses.