Shedding Light on the Black Box: Explaining Deep Neural Network Prediction of Clinical Outcomes.

ABSTRACT: Deep neural network models are emerging as an important method in healthcare delivery, following the recent success in other domains such as image recognition. Due to the multiple non-linear inner transformations, deep neural networks are viewed by many as black boxes. For practical use, deep learning models require explanations that are intuitive to clinicians. In this study, we developed a deep neural network model to predict outcomes following major cardiovascular procedures, using temporal image representation of past medical history as input. We created a novel explanation for the prediction of the model by defining impact scores that associate clinical observations with the outcome. For comparison, a logistic regression model was fitted to the same dataset. We compared the impact sco

SUBMITTER: Shao Y 

PROVIDER: S-EPMC7983057 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature