Boggaram Ravishankar on Muck Rack

Boggaram Ravishankar

As seen in: Biomed Central (BMC)
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Articles

Analysis of RNA-Seq data using self-supervised learning for vital status prediction of colorectal cancer patients - BMC Bioinformatics

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By Murali Krishna, Om Amitesh, Boggaram Ravishankar
| Biomed Central (BMC)
Interpretability This study makes use of model interpretability, which helps quantify and visualise the effect of features in the dataset, i.e., the gene expressions to the vital status predicted by the models used. As elucidated in the previous sections, TabNet is the best-performing model in our study with a final ROC-AUC score of 0.842 on RNA-Seq data (unimodal data) and 0.88 on multimodal data.
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