Anonymized images from 5 fat-suppressed (SPAIR) sequences and 1 non-suppressed sequence acquired on 5 head and neck cancer patients on the Unity MR-Linac
Background and PurposeMachine learning (ML) is emerging as a feasible approach to optimize patients’ care path in Radiation Oncology. Applications include autosegmentation, treatment planning optimiza
Pain data for paper publication: Salama V, Youssef S, Xu T, Wahid KA, PhD, Chen J, Rigert J, Lee A, Hutcheson KA, Gunn B, Phan J, Garden AS, Frank SJ, Morrison W, Reddy JP, Spiotto MT, Naser MA,
Anonymized public clinical, dose-volume, and DIGEST outcome data, as detailed in Kamal et al. (PMID: 29961581; PMCID: PMC6595477). Data consists of 3 txt files encoded as csv files: 1 detailing clinic
