Deep learning radiomics model related with genomics phenotypes for lymph node metastasis prediction in colorectal cancer
Description
This repository is the implementation of the paper " Deep learning radiomics model related with genomics phenotypes for lymph node metastasis prediction in colorectal cancer".
Contents
This repository contains the code about developing the model, assessing the performance of model, transcript analysis (GO and KEGG analysis), and the correlation analysis.
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model developed and validated.R: developed the model through
LASSO
and5 fold cross validation
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Assessment of model.R: including the calibrate cure and decision curve analysis.
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Correlation analysis.R: including the correlation analysis of DPL features and genes, the correlation of DPL score and clinical characteristic.
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Transcript analysis.R: including the differential expressed genes, GO analysis, and KEGG analysis.
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Univarible and multivariable analysis.R: including the univarible and multivariable analysis of DPL features and top differential expressed genes for predicting the LNM.
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AI Model: including the python codes of extracting DPL features by using AutoEncoder.
Dataset
Due to privacy restrictions, we don’t upload our data used in the paper. If you are interested in our paper, please contact us.
Cite
If you use our code, please cite: