DeepFeature: feature selection in nonimage data using convolutional neural network.

ABSTRACT: Artificial intelligence methods offer exciting new capabilities for the discovery of biological mechanisms from raw data because they are able to detect vastly more complex patterns of association that cannot be captured by classical statistical tests. Among these methods, deep neural networks are currently among the most advanced approaches and, in particular, convolutional neural networks (CNNs) have been shown to perform excellently for a variety of difficult tasks. Despite that applications of this type of networks to high-dimensional omics data and, most importantly, meaningful interpretation of the results returned from such models in a biomedical context remains an open problem. Here we present, an approach applying a CNN to nonimage data for feature selection. Our pipeline, DeepFea

SUBMITTER: Sharma A 

PROVIDER: S-EPMC8575039 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature