XMR: an explainable multimodal neural network for drug response prediction.

ABSTRACT: Introduction: Existing large-scale preclinical cancer drug response databases provide us with a great opportunity to identify and predict potentially effective drugs to combat cancers. Deep learning models built on these databases have been developed and applied to tackle the cancer drug-response prediction task. Their prediction has been demonstrated to significantly outperform traditional machine learning methods. However, due to the "black box" characteristic, biologically faithful explanations are hardly derived from these deep learning models. Interpretable deep learning models that rely on visible neural networks (VNNs) have been proposed to provide biological justification for the predicted outcomes. However, their performance does not meet the expectation to be applied in cl

SUBMITTER: Wang Z 

PROVIDER: S-EPMC10433751 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature