Differentiating between liver diseases by applying multiclass machine learning approaches to transcriptomics of liver tissue or blood-based samples
AC, alcohol-associated cirrhosis, AH, alcohol-associated hepatitis, AKR1B10, aldo-keto reductase family 1 member B10, BTM, blood transcription module, Classification, DE, differential expression, FPKM, fragments per kilobase of exon model per million reads mapped, GSEA, gene set-enrichment analysis, IG, information gain, IPA, Ingenuity Pathway Analysis, LR, logistic regression, LTCDS, liver tissue cell distribution system, LV, liver tissue, ML, machine learning, MMP, matrix metalloproteases, NAFLD, non-alcohol-associated fatty liver disease, PBMCs, peripheral blood mononuclear cells, RNA sequencing, RNA-seq, RNA sequencing, SCAHC, Southern California Alcoholic Hepatitis Consortium, SVM, support vector machine, TNF, tumor necrosis factor, alcohol-associated liver disease, biomarker discovery, kNN, k-nearest neighbors,
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