568 citations · 693 across the 20 of their papers we have counts for
7 papers · 1 filter
MedShift: identifying shift data for medical dataset curation
Xiaoyuan Guo, Judy Wawira Gichoya, Hari Trivedi +2
To curate a high-quality dataset, identifying data variance between the internal and external sources is a fundamental and crucial step. However, methods to detect shift or varianc…
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…
Two-step adversarial debiasing with partial learning -- medical image case-studies
Ramon Correa, Jiwoong Jason Jeong, Bhavik Patel +3
The use of artificial intelligence (AI) in healthcare has become a very active research area in the last few years. While significant progress has been made in image classification…
CVAD: A generic medical anomaly detector based on Cascade VAE
Xiaoyuan Guo, Judy Wawira Gichoya, Saptarshi Purkayastha +1
Detecting out-of-distribution (OOD) samples in medical imaging plays an important role for downstream medical diagnosis. However, existing OOD detectors are demonstrated on natural…
Margin-Aware Intra-Class Novelty Identification for Medical Images
Xiaoyuan Guo, Judy Wawira Gichoya, Saptarshi Purkayastha +1
Traditional anomaly detection methods focus on detecting inter-class variations while medical image novelty identification is inherently an intra-class detection problem. For examp…
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…
PAC-Bayes Bounds on Variational Tempered Posteriors for Markov Models
Imon Banerjee, Vinayak A. Rao, Harsha Honnappa
Datasets displaying temporal dependencies abound in science and engineering applications, with Markov models representing a simplified and popular view of the temporal dependence s…