568 citations · 733 across the 23 of their papers we have counts for
5 papers · 1 filter
Few-Shot Transfer Learning to improve Chest X-Ray pathology detection using limited triplets
Ananth Reddy Bhimireddy, John Lee Burns, Saptarshi Purkayastha +1
Deep learning approaches applied to medical imaging have reached near-human or better-than-human performance on many diagnostic tasks. For instance, the CheXpert competition on det…
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…
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…
Was there COVID-19 back in 2012? Challenge for AI in Diagnosis with Similar Indications
Imon Banerjee, Priyanshu Sinha, Saptarshi Purkayastha +5
Purpose: Since the recent COVID-19 outbreak, there has been an avalanche of research papers applying deep learning based image processing to chest radiographs for detection of the…
A DICOM Framework for Machine Learning Pipelines against Real-Time Radiology Images
Pradeeban Kathiravelu, Puneet Sharma, Ashish Sharma +7
Executing machine learning (ML) pipelines in real-time on radiology images is hard due to the limited computing resources in clinical environments and the lack of efficient data tr…