Basu Lab Research Test

Leveraging Artificial Intelligence and Machine Learning Methodology to Advance Cancer Research

Modern cancer therapies have dramatically improved outcomes, but they also introduce complex and sometimes long-lasting side effects that can impact quality of life long after treatment ends. Our research uses artificial intelligence (AI) and machine learning (ML) to better understand why patients experience toxicities differently—and how symptoms evolve over time—so that supportive care and treatment planning can become more proactive, personalized, and effective.

We develop computational models that integrate clinical factors, patient-reported outcomes (PROs), laboratory biomarkers, and germline genetic information to predict which patients are most likely to experience significant toxicity or declines in quality of life. By combining longitudinal symptom tracking with biologic and genetic signals, our goal is to identify early warning patterns and build decision-support tools that help clinicians optimize therapy while minimizing long-term harm.