14 citations · 19 across the 5 of their papers we have counts for
5 papers
Improving Pneumonia Localization via Cross-Attention on Medical Images and Reports
Riddhish Bhalodia, Ali Hatamizadeh, Leo Tam +4
Localization and characterization of diseases like pneumonia are primary steps in a clinical pipeline, facilitating detailed clinical diagnosis and subsequent treatment planning. A…
Self-supervised Image-text Pre-training With Mixed Data In Chest X-rays
Xiaosong Wang, Ziyue Xu, Leo Tam +2
Pre-trained models, e.g., from ImageNet, have proven to be effective in boosting the performance of many downstream applications. It is too demanding to acquire large-scale annotat…
Transformer Query-Target Knowledge Discovery (TEND): Drug Discovery from CORD-19
Leo K. Tam, Xiaosong Wang, Daguang Xu
Previous work established skip-gram word2vec models could be used to mine knowledge in the materials science literature for the discovery of thermoelectrics. Recent transformer arc…
Learning Image Labels On-the-fly for Training Robust Classification Models
Xiaosong Wang, Ziyue Xu, Dong Yang +3
Current deep learning paradigms largely benefit from the tremendous amount of annotated data. However, the quality of the annotations often varies among labelers. Multi-observer st…
Weakly supervised one-stage vision and language disease detection using large scale pneumonia and pneumothorax studies
Leo K. Tam, Xiaosong Wang, Evrim Turkbey +3
Detecting clinically relevant objects in medical images is a challenge despite large datasets due to the lack of detailed labels. To address the label issue, we utilize the scene-l…