6 citations · 9 across the 3 of their papers we have counts for
4 papers
MaxCorrMGNN: A Multi-Graph Neural Network Framework for Generalized Multimodal Fusion of Medical Data for Outcome Prediction
Niharika S. D'Souza, Hongzhi Wang, Andrea Giovannini +4
With the emergence of multimodal electronic health records, the evidence for an outcome may be captured across multiple modalities ranging from clinical to imaging and genomic data…
Fusing Modalities by Multiplexed Graph Neural Networks for Outcome Prediction in Tuberculosis
Niharika S. D'Souza, Hongzhi Wang, Andrea Giovannini +4
In a complex disease such as tuberculosis, the evidence for the disease and its evolution may be present in multiple modalities such as clinical, genomic, or imaging data. Effectiv…
Extracting and Learning Fine-Grained Labels from Chest Radiographs
Tanveer Syeda-Mahmood, Ph. D, K. C. L Wong +6
Chest radiographs are the most common diagnostic exam in emergency rooms and intensive care units today. Recently, a number of researchers have begun working on large chest X-ray d…
Chest X-ray Report Generation through Fine-Grained Label Learning
Tanveer Syeda-Mahmood, Ken C. L. Wong, Yaniv Gur +9
Obtaining automated preliminary read reports for common exams such as chest X-rays will expedite clinical workflows and improve operational efficiencies in hospitals. However, the…