Cancer type classification
3 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Cancer type classification
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TCGA
Most implemented papers
SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification
In our project, we extend the idea of using a VAE model for low dimensional latent space extraction with the self-supervised learning technique of feature subsetting.
Analyzing RNA-Seq Gene Expression Data Using Deep Learning Approaches for Cancer Classification
Celtyee/RNA-seq-Cancer-classfication
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Applied Sciences 2022
To perform multiple cancer type classification and to find differentially expressed genes, data for multiple cancer types need to be analyzed.
Self-omics: A Self-supervised Learning Framework for Multi-omics Cancer Data
Lack of annotated data is a significant problem in machine learning, and Self-Supervised Learning (SSL) methods are typically used to deal with limited labelled data.
