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
Zhang Y, Winter A, Ficociello LH, Arya S, Stuard S, Usvyat LA, Kalantar-Zadeh K. Hemodialysis Modality and Mortality Outcomes among Incident Dialysis Patients: An International[...]
Budoff MJ. Lessons From the Past. J Soc Cardiovasc Angiogr Interv. 2026 Mar 12;5(4):104276. doi: 10.1016/j.jscai.2026.104276. PMID: 42111096; PMCID: PMC13154623.
Chen J, Tian L, Bundy JD, Jaeger BC, Zhang R, Li C, He H, Kumbala D, Chen CS, Garimella PS, Townsend RR, Rahman M, Jaar[...]