Deep Learning Based Recurrence Prediction in Head and Neck Cancers after Radiotherapy
Nearly half of patients with head and neck (H&N) cancers experience recurrence, yet the challenge of prognosticating high-risk individuals for intensified radiotherapy persists. Here we aimed to develop a deep learning (DL) model for predicting H&N cancer recurrence based on clinical and radiomic features (texture, shape, intensity) from radiation planning CT simulation scans.
Source: International Journal of Radiation Oncology * Biology * Physics - Category: Radiology Authors: M.I. Parker, W.W. Su, M. Kang, Y. Yuan, V. Gupta, J.T. Liu, K. Sindhu, E. Genden, R.L. Bakst Tags: 211 Source Type: research
More News: Biology | Cancer | Cancer & Oncology | Head and Neck Cancer | Learning | PET Scan | Physics | Radiology | Universities & Medical Training