68 citations · 82 across the 5 of their papers we have counts for
6 papers
LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype
Vivek Shankar, Xiaoli Yang, Vrishab Krishna +10
The accurate classification of lymphoma subtypes using hematoxylin and eosin (H&E)-stained tissue is complicated by the wide range of morphological features these cancers can exhib…
How to Train Your CheXDragon: Training Chest X-Ray Models for Transfer to Novel Tasks and Healthcare Systems
Cara Van Uden, Jeremy Irvin, Mars Huang +4
Self-supervised learning (SSL) enables label efficient training for machine learning models. This is essential for domains such as medical imaging, where labels are costly and time…
Deep Learning-Based Sparse Whole-Slide Image Analysis for the Diagnosis of Gastric Intestinal Metaplasia
Jon Braatz, Pranav Rajpurkar, Stephanie Zhang +2
In recent years, deep learning has successfully been applied to automate a wide variety of tasks in diagnostic histopathology. However, fast and reliable localization of small-scal…
Q-Pain: A Question Answering Dataset to Measure Social Bias in Pain Management
Cécile Logé, Emily Ross, David Yaw Amoah Dadey +4
Recent advances in Natural Language Processing (NLP), and specifically automated Question Answering (QA) systems, have demonstrated both impressive linguistic fluency and a pernici…
RadGraph: Extracting Clinical Entities and Relations from Radiology Reports
Saahil Jain, Ashwin Agrawal, Adriel Saporta +9
Extracting structured clinical information from free-text radiology reports can enable the use of radiology report information for a variety of critical healthcare applications. In…
3KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentations
Bryan Gopal, Ryan W. Han, Gautham Raghupathi +3
We propose 3KG, a physiologically-inspired contrastive learning approach that generates views using 3D augmentations of the 12-lead electrocardiogram. We evaluate representation qu…