Cluster-Based Toxicity Estimation of Osteoradionecrosis via Unsupervised Machine Learning: Moving Beyond Single Dose-Parameter Normal Tissue Complication Probability by Using Whole Dose-Volume Histograms for Cohort Risk Stratification

Given the limitations of extant models for normal tissue complication probability estimation for osteoradionecrosis (ORN) of the mandible, the purpose of this study was to enrich statistical inference by exploiting structural properties of data and provide a clinically reliable model for ORN risk evaluation through an unsupervised-learning analysis that incorporates the whole radiation dose distribution on the mandible.

Source: International Journal of Radiation Oncology * Biology * Physics - March 8, 2024 Category: Radiology Authors: Seyedmohammadhossein Hosseinian, Mehdi Hemmati, Cem Dede, Travis C. Salzillo, Lisanne V. van Dijk, Abdallah S.R. Mohamed, Stephen Y. Lai, Andrew J. Schaefer, Clifton D. Fuller, Rice/MD Anderson Center for Operations Research in Cancer (CORC) and MD Anders Tags: Physics Contribution Source Type: research