3 papers
eess.IV2021
Attention-based Multi-scale Gated Recurrent Encoder with Novel Correlation Loss for COVID-19 Progression Prediction
Aishik Konwer, Joseph Bae, Gagandeep Singh +5
COVID-19 image analysis has mostly focused on diagnostic tasks using single timepoint scans acquired upon disease presentation or admission. We present a deep learning-based approa…
eess.IV2021
Attention based CNN-LSTM Network for Pulmonary Embolism Prediction on Chest Computed Tomography Pulmonary Angiograms
Sudhir Suman, Gagandeep Singh, Nicole Sakla +5
With more than 60,000 deaths annually in the United States, Pulmonary Embolism (PE) is among the most fatal cardiovascular diseases. It is caused by an artery blockage in the lung;…
q-bio.QM2020
Predicting Clinical Outcomes in COVID-19 using Radiomics and Deep Learning on Chest Radiographs: A Multi-Institutional Study
Joseph Bae, Saarthak Kapse, Gagandeep Singh +10
We predict mechanical ventilation requirement and mortality using computational modeling of chest radiographs (CXRs) for coronavirus disease 2019 (COVID-19) patients. This two-cent…