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
Salih H, Samadzadeh S, Bereuter C, Motamedi S, Chien C, Villoslada P, Stiebel-Kalish H, Asgari N, Mao-Draayer Y, Ringelstein M, Havla J, Peixoto MAL, Kim[...]
McLaughlin VV, Howard L, Elwing J, Fernandes CC, Gaine S, Galiè N, Oudiz RJ, Stefani M, Stickel S, Strachan P, Tamura Y, Kim NH. Evaluating[...]
Duberstein ZT, Murphy H, Wu Q, Meng Y, Wang C, Smith R, Salafia C, Chowdhury SF, Barrett E, Scheible K, Qiu X, O'Connor TG. Do[...]