An Integrated Deep Learning Framework for Small-Sample Biomedical Data Classification: Explainable Graph Neural Networks with Data Augmentation for RNA sequencing Dataset

2026-02-24 genetic and genomic medicine Title + abstract only

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Applying deep learning models to RNA-Seq data poses substantial challenges, primarily due to the high dimensionality of the data and the limited sample sizes. To address these issues, this study introduces an advanced deep learning pipeline that integrates feature engineering with data augmentation. The engineering application focuses on biomedical engineering, specifically the classification of RNA-Seq datasets for disease diagnosis. The proposed framework was initially validated on synthetic d...

An Integrated Deep Learning Framework for Small-Sample Biomedical Data Classification: Explainable Graph Neural Networks with Data Augmentation for RNA sequencing Dataset

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