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,
Related Posts
Budoff MJ, Verghese D, Kinninger A, Lakshmanan S. Plaque, P-Values, and Presentation Bias: Four Limitations of the EKSTROM Trial. Eur Heart J Cardiovasc Imaging. 2026[...]
Chan LC, Lee HK, Wang L, Wang H, Filler SG, Ciranna A, Abdelhady W, Xiong YQ, Li L, Gonzales RA, Ruffin F, Fowler VG Jr,[...]
Colasurdo JR, Yamamoto N, Kinninger A, Budoff MJ, Roy SK. Coronary computed tomography angiography versus functional testing in a multi-ethnic urban county population. Coron Artery[...]