activity
20212023
most citedReading Race: AI Recognises Patient's Racial Identity In Medical Images

568 citations · 792 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2023★ 1 cited

LOVM: Language-Only Vision Model Selection

Orr Zohar, Shih-Cheng Huang, Kuan-Chieh Wang +1

Pre-trained multi-modal vision-language models (VLMs) are becoming increasingly popular due to their exceptional performance on downstream vision applications, particularly in the…

eess.IV2023★ 3 cited

Video Pretraining Advances 3D Deep Learning on Chest CT Tasks

Alexander Ke, Shih-Cheng Huang, Chloe P O'Connell +3

Pretraining on large natural image classification datasets such as ImageNet has aided model development on data-scarce 2D medical tasks. 3D medical tasks often have much less data…

cs.CV2023★ 10 cited

BenchMD: A Benchmark for Unified Learning on Medical Images and Sensors

Kathryn Wantlin, Chenwei Wu, Shih-Cheng Huang +12

Medical data poses a daunting challenge for AI algorithms: it exists in many different modalities, experiences frequent distribution shifts, and suffers from a scarcity of examples…

cs.LG2023★ 2 cited

Diagnosing and Rectifying Vision Models using Language

Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang +3

Recent multi-modal contrastive learning models have demonstrated the ability to learn an embedding space suitable for building strong vision classifiers, by leveraging the rich inf…

cs.CV2022★ 182 cited

Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging

Rui Yan, Liangqiong Qu, Qingyue Wei +5

The collection and curation of large-scale medical datasets from multiple institutions is essential for training accurate deep learning models, but privacy concerns often hinder da…

eess.IV2021★ 24 cited

RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and EHR

Yuyin Zhou, Shih-Cheng Huang, Jason Alan Fries +8

Despite the routine use of electronic health record (EHR) data by radiologists to contextualize clinical history and inform image interpretation, the majority of deep learning arch…

eess.IV2021★ 2 cited

OncoNet: Weakly Supervised Siamese Network to automate cancer treatment response assessment between longitudinal FDG PET/CT examinations

Anirudh Joshi, Sabri Eyuboglu, Shih-Cheng Huang +5

FDG PET/CT imaging is a resource intensive examination critical for managing malignant disease and is particularly important for longitudinal assessment during therapy. Approaches…

cs.CV2021★ 568 cited

Reading Race: AI Recognises Patient's Racial Identity In Medical Images

Imon Banerjee, Ananth Reddy Bhimireddy, John L. Burns +20

Background: In medical imaging, prior studies have demonstrated disparate AI performance by race, yet there is no known correlation for race on medical imaging that would be obviou…