3 citations · 12 across the 12 of their papers we have counts for
17 papers
A Trustworthy Framework for Medical Image Analysis with Deep Learning
Kai Ma, Siyuan He, Pengcheng Xi +3
Computer vision and machine learning are playing an increasingly important role in computer-assisted diagnosis; however, the application of deep learning to medical imaging has cha…
COVID-Net Assistant: A Deep Learning-Driven Virtual Assistant for COVID-19 Symptom Prediction and Recommendation
Pengyuan Shi, Yuetong Wang, Saad Abbasi +1
As the COVID-19 pandemic continues to put a significant burden on healthcare systems worldwide, there has been growing interest in finding inexpensive symptom pre-screening and rec…
COVID-Net UV: An End-to-End Spatio-Temporal Deep Neural Network Architecture for Automated Diagnosis of COVID-19 Infection from Ultrasound Videos
Hilda Azimi, Ashkan Ebadi, Jessy Song +2
Besides vaccination, as an effective way to mitigate the further spread of COVID-19, fast and accurate screening of individuals to test for the disease is yet necessary to ensure p…
COVID-Net US-X: Enhanced Deep Neural Network for Detection of COVID-19 Patient Cases from Convex Ultrasound Imaging Through Extended Linear-Convex Ultrasound Augmentation Learning
E. Zhixuan Zeng, Adrian Florea, Alexander Wong
As the global population continues to face significant negative impact by the on-going COVID-19 pandemic, there has been an increasing usage of point-of-care ultrasound (POCUS) ima…
ICDBigBird: A Contextual Embedding Model for ICD Code Classification
George Michalopoulos, Michal Malyska, Nicola Sahar +2
The International Classification of Diseases (ICD) system is the international standard for classifying diseases and procedures during a healthcare encounter and is widely used for…
Improving Classification Model Performance on Chest X-Rays through Lung Segmentation
Hilda Azimi, Jianxing Zhang, Pengcheng Xi +4
Chest radiography is an effective screening tool for diagnosing pulmonary diseases. In computer-aided diagnosis, extracting the relevant region of interest, i.e., isolating the lun…