Mussie Alemayehu, Gebregizabeher Yohannes, Ashenafi Damte, Atsede Fantahun, Kahsu Gebrekirstos, Resom Tsegay, Adina Goldberger, Henock Yebyo
Prevalence and predictors of sexual violence among commercial sex workers in Northern Ethiopia
Reproductive health
today colorectal cancer crc diagnosis performed using colonoscopy current effective screening method however colonoscopy poses risks harm patient invasive process recent research proven metabolomics potential noninvasive detection method use identified biomarkers detect potential cancer patients body aim study develop machinelearning ml model based chemical descriptors recognize crcassociated metabolites selected set metabolites found biomarkers crc confirmed participate cancerrelated pathways used training machinelearning model diagnostics crc using set selective metabolites random compounds developed range ml models best performing ml model trained stage 02 crc metabolite data predicted metabolite class 8955 accuracy best performing ml model trained stage 34 crc metabolite data predicted metabolite class 9521 accuracy lastly bestperforming ml model trained stage 04 crc metabolite data predicted metabolite class 9304 accuracy models tested independent datasets including random unrelateddisease metabolites addition six pathways related crc metabolites also distinguished aminoacyltrna biosynthesis glyoxylate dicarboxylate metabolism glycine serine threonine metabolism phenylalanine tyrosine tryptophan biosynthesis arginine biosynthesis alanine aspartate glutamate metabolism thus research study created machinelearning models based metaboliterelated descriptors may helpful developing noninvasive diagnosis method crc