Supplementary Table S1-S3 from Predicting Molecular Subtype and Survival of Rhabdomyosarcoma Patients Using Deep Learning of H&E Images: A Report from the Children's Oncology Group
Year: 2023
Type: supplementary-materials
Abstract: Supplemental Table S1. Whole slide image tissue segmentation statistics by an expert pathologist and probability prediction using a trained convolutional neural network. Supplemental Table S2. Clinical and molecular characteristics of FN-RMS samples used for training models for mutation prediction. Yellow boxes indicate genes included in defining the RAS pathway. Supplemental Table S3. Clinical information with COG risk stratification of FN-RMS samples used for training a prognostication predictive CNN.
Authors: David Milewski, Hyun Jung, G. Thomas Brown, Yanling Liu, Ben Somerville, Curtis Lisle, Marc Ladanyi, Erin R. Rudzinski, Hyoyoung Choo-Wosoba, Donald A. Barkauskas, Tammy Lo, David Hall, Corinne M. Linardic, Jun S. Wei, Hsien-Chao Chou, Stephen X. Skapek, Rajkumar Venkatramani, Peter K. Bode, Seth M. Steinberg, George Zaki, Igor B. Kuznetsov, Douglas S. Hawkins, Jack F. Shern, Jack Collins, Javed Khan
Language: English
Topic: AI in cancer detection
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4361967405