Sepinoud Azimi

Robust and Quality-of-Life-Aware Treatment Protocols in NSCLC using Deep Reinforcement Learning

This study uses deep reinforcement learning to design treatment protocols for NSCLC that improve robustness, quality of life, and time to progression compared to standard adaptive therapy and maximum tolerable dose approaches.

Migrastatic Therapy as a Potential Game-Changer inAdaptive Cancer Treatment

This study proposes integrating migrastatics into adaptive therapy to delay metastasis and improve cancer treatment outcomes.