GevaertLab

MultimodalPrognosis

Deep Learning with Multimodal Representation for Pancancer Prognosis Prediction

DAPL

Autoencoder network for imputing missing values

GBM360

Spatial cellular architecture predicts prognosis in glioblastoma - Nature Communications

MultiModalBrainSurvival

AMARETTO

Regulatory network inference and driver gene evaluation using integrative multi-omics analysis and penalized regression

metalearning_survival

RNA-GAN

Synthetic whole-slide imaging tile generation with gene expression profiles infused deep generative models - Cell Reports Methods

MethylMix

Identification of differentially methylated genes in biomedical data

BetaVAEImputation

radiomics_pipeline

sequoia-pub

SEQUOIA: Digital profiling of cancer transcriptomes with grouped vision attention

RNASeq_pipeline

Variational-Auto-Encoder

miccai-cpm-ensemble

MICCAI 2018 Computational Precision Medicine Challenge: Combined Pathology and Radiology Classification

EpiMix

LungNet

Predicting overall survival for lung cancer patients using deep learning on lung CTs

methylation-based-diagnostic-signature-to-distinguish-renal-cell-carcinoma-from-oncocytoma

R code for manuscript: 'Development of a DNA methylation-based diagnostic signature to distinguish renal cell carcinoma from benign oncocytoma'

.github

EpiMix.data

Supporting experiment data package for the EpiMix R package.

lncRNA_pancancer

lncRNA gene expression profiles for tumor samples from TCGA

ProteoMix

Roche-Project