15 citations · 48 across the 9 of their papers we have counts for
4 papers · 1 filter
Learn-By-Calibrating: Using Calibration as a Training Objective
Jayaraman J. Thiagarajan, Bindya Venkatesh, Deepta Rajan
Calibration error is commonly adopted for evaluating the quality of uncertainty estimators in deep neural networks. In this paper, we argue that such a metric is highly beneficial…
Pi-PE: A Pipeline for Pulmonary Embolism Detection using Sparsely Annotated 3D CT Images
Deepta Rajan, David Beymer, Shafiqul Abedin +1
Pulmonary embolisms (PE) are known to be one of the leading causes for cardiac-related mortality. Due to inherent variabilities in how PE manifests and the cumbersome nature of man…
Leveraging Medical Visual Question Answering with Supporting Facts
Tomasz Kornuta, Deepta Rajan, Chaitanya Shivade +2
In this working notes paper, we describe IBM Research AI (Almaden) team's participation in the ImageCLEF 2019 VQA-Med competition. The challenge consists of four question-answering…
Generalization Studies of Neural Network Models for Cardiac Disease Detection Using Limited Channel ECG
Deepta Rajan, David Beymer, Girish Narayan
Acceleration of machine learning research in healthcare is challenged by lack of large annotated and balanced datasets. Furthermore, dealing with measurement inaccuracies and explo…