Deep Learning for Medical Imaging From Diagnosis Prediction to its Counterfactual Explanation

09/07/2022
by   Sumedha Singla, et al.
0

Deep neural networks (DNN) have achieved unprecedented performance in computer-vision tasks almost ubiquitously in business, technology, and science. While substantial efforts are made to engineer highly accurate architectures and provide usable model explanations, most state-of-the-art approaches are first designed for natural vision and then translated to the medical domain. This dissertation seeks to address this gap by proposing novel architectures that integrate the domain-specific constraints of medical imaging into the DNN model and explanation design.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset