Chris Thomas

Chris Thomas is a researcher specializing in radiation therapy and medical imaging applications. His work focuses on advancing treatment planning techniques using artificial intelligence and improving outcomes through precision oncology. He has contributed to studies on immune response mechanisms in severe COVID-19 cases and post-pandemic respiratory recovery. His research bridges clinical practice and technological innovation in radiotherapy.

Research interests include radiation dosimetry optimization, PET/MRI integration in treatment planning, and clinical trial methodologies for oncological interventions. Notably, his doctoral thesis developed deep learning approaches to reduce gastrointestinal toxicity in pelvic radiotherapy.

Recent publications explore neural network-driven dose-prediction models, PET-guided radiotherapy protocols, and immune system aging's role in disease severity. Collaborations span oncology, radiology, and computational biology disciplines.