Thomas Desilvio

Spatial attention wavelon network (SpAWN) for survival-based risk stratification in kidney cancers via CT

Human-in-the-loop informed deep learning rectal tumor segmentation on pre-treatment MRI

Intra-and peri-tumoral radiomic features are predictive of pathologic response to multiple neoadjuvant therapy regimen in rectal cancers via pre-treatment MRI

Deep learning based risk stratification of pre-operative CT scans is prognostic of overall survival in kidney cancers

Hybrid convolutional wavelet networks for predicting treatment response via radiological images of bowel disease

CohortFinder: an open-source tool for data-driven partitioning of biomedical image cohorts to yield robust machine learning models

Region-specific deep learning models for accurate segmentation of rectal structures on post-chemoradiation T2w MRI: a multi-institutional, multi-reader study

Integrating multi-plane and multi-region radiomic features to predict pathologic response to neoadjuvant chemoradiation in rectal cancers via pre-treatment MRI