Characterization of signature trends across the spectrum of non-alcoholic fatty liver disease using deep learning method

Abstract excerpt

AIMS: The timely diagnosis of different stages in NAFLD is crucial for disease treatment and reversal. We used hepatocellular ballooning to determine different NAFLD stages. MAIN METHODS: We analyzed differentially expressed genes (DEGs) in 78 patients with NAFLD and in healthy controls from previously published RNA-seq data. We identified two expression types in NAFLD progression, calculated the predictive power...

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