This concentration explores how AI is transforming medicine from computer vision models in radiology and pathology, to natural language processing in clinical documentation, to AI-driven drug discovery, while ensuring students develop a principled framework for evaluating algorithmic bias, data privacy, regulatory considerations, and the human dimensions of AI-assisted care.

Curriculum

Students in the aiSC attend monthly meetings that combine didactic seminars, journal club discussions, hands-on AI demonstrations, guest speakers from academia and industry, and student research presentations. Monthly sessions are deliberately integrated across all four years so students from all levels learn together, fostering mentorship and collaborative learning.

Core content areas across the four years include: introduction to AI/ML fundamentals for clinicians, clinical AI applications (imaging AI, clinical NLP, predictive models), AI research methodology and study design, AI ethics and regulatory frameworks, algorithmic bias and health equity, and capstone research development.

Faculty Leadership

Srinivas Bharadwaj, PhD
Ambuj Kumar, PhD
Shane Puckett, EdD