Encrypted | Login

2021 AAPM Virtual 63rd Annual Meeting - Session: Data Science, Radiomics, and Computing Q & A

This video is currently visible only to AAPM Members, Affiliates and Developing Country Educational Associates. Embargo periods are typically one year from the date the presentation was first published.

Q & A

When you have finished the video, you may watch again, browse/search all videos, go back to the previous page, or watch another video in this session (see below). add this video to a playlist.

All videos in this session:
A Multi-Modality Radiomics-Based Model for Recurrence Risk Stratification in Non-Small Cell Lung Cancer - Jaryd Christie Western University
Computer-Assisted Diagnosis of Hepatic Portal Hypertension: A Novel, Attention-Guided Deep Learning Framework Based On CT Imaging and Laboratory Data Integration - Yuqi Wang Duke University
JACK KROHMER EARLY-CAREER INVESTIGATOR COMPETITION WINNER: Multi-Group Multi-Block Data Integration for Harmonizing 18F-FDG-PET/CT Radiomics Associated with Circulating Tumor Cells and Predicting Recurrence-Free Survival Across Independent Lung Cancer Radiotherapy Studies - Sang Ho Lee, PhD University of Pennsylvania
Multi-Institutional Data Analysis of Radiomic Signature Set to Predict Overall Survival in Glioblastoma Patients - Eric Carver Wayne State University
Multi-Class Classification Based On Multi-Loss Strategy and Auxiliary Deep Learning Network with Applications in Medical Imaging - Zong Fan University of Illinois Urbana-Champaign
A Radiomics-Boosted Deep Learning Model for COVID-19 and Non-COVID-19 Pneumonia Detection Using Chest X-Ray Image - Zongsheng Hu Duke Kunshan University
Spatial Reconstruction of Statistically Significant Radiomics Signatures Using 3D Wavelet Decomposition in Tumors of Oropharyngeal Cancer - Hassan Bagher-Ebadian Henry Ford Health System
Graph includes member loads and non-member loads (0 total loads). Exclude non-member? A load is defined as someone coming to this page, not necesarily that they pressed play, or watched the entire presentation.