DeeP4med: deep learning for P4 medicine to predict normal and cancer transcriptome in multiple human tissues.

ABSTRACT:

Background

P4 medicine (predict, prevent, personalize, and participate) is a new approach to diagnosing and predicting diseases on a patient-by-patient basis. For the prevention and treatment of diseases, prediction plays a fundamental role. One of the intelligent strategies is the design of deep learning models that can predict the state of the disease using gene expression data.

Results

We create an autoencoder deep learning model called DeeP4med, including a Classifier and a Transferor that predicts cancer's gene expression (mRNA) matrix from its matched normal sample and vice versa. The range of the F1 score of the model, depending on tissue type in the Classifier, is from 0.935 to 0.999 and in Transferor from 0.944 to 0.999. The accuracy of DeeP4med for tissue and disea

SUBMITTER: Mahdi-Esferizi R 

PROVIDER: S-EPMC10320882 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature