DEVELOPING MULTIMODAL ANALYSIS DEEP LEARNING TO PREDICT TREATMENT TOXICITIES AND RESPONSE FOR PERSONALIZED TREATMENTS
New York, NY
An opening is now available for a postdoctoral researcher in the department of medical physics for individuals interested in developing deep learning methods to combine longitudinal information to predict treatment response and toxicities in lung cancer patients. The two‑year project involves enhancing existing and developing new methods to integrate multiple sources of information including clinical text, diagnostic CTs, and weekly cone beam CTs to derive biomarkers of treatment response and normal tissue toxicity. The current database exceeds over 2,000 patients, with several patients containing multiple follow‑up scans acquired during the course of radiation and systemic therapies.
The project will involve working with a multi‑disciplinary team of computer scientists,...