13 citations · 13 across the 1 of their papers we have counts for
4 papers
Using Causal Analysis for Conceptual Deep Learning Explanation
Sumedha Singla, Stephen Wallace, Sofia Triantafillou +1
Model explainability is essential for the creation of trustworthy Machine Learning models in healthcare. An ideal explanation resembles the decision-making process of a domain expe…
Self-Supervised Vessel Enhancement Using Flow-Based Consistencies
Rohit Jena, Sumedha Singla, Kayhan Batmanghelich
Vessel segmentation is an essential task in many clinical applications. Although supervised methods have achieved state-of-art performance, acquiring expert annotation is laborious…
Explanation by Progressive Exaggeration
Sumedha Singla, Brian Pollack, Junxiang Chen +1
As machine learning methods see greater adoption and implementation in high stakes applications such as medical image diagnosis, the need for model interpretability and explanation…
Subject2Vec: Generative-Discriminative Approach from a Set of Image Patches to a Vector
Sumedha Singla, Mingming Gong, Siamak Ravanbakhsh +3
We propose an attention-based method that aggregates local image features to a subject-level representation for predicting disease severity. In contrast to classical deep learning…