Application of Multi-SNP Approaches Bayesian LASSO and AUC-RF to Detect Main Effects of Inflammatory-Gene Variants Associated with Bladder Cancer Risk - de Maturana, Evangelina López; Ye, Yuanqing; Calle, M. Luz; Rothman, Nathaniel; Urrea, Víctor; Kogevinas, Manolis; Petrus, Sandra; Chanock, Stephen J.; Tardón, Adonina; García-Closas, Montserrat; González-Neira, Anna; Vellalta, Gemma; et al. (PloS one, 2013)
Keywords: Adult; Aged; Aged, 80 and over; Algorithms; Artificial Intelligence; Bayes Theorem; Bayesian analysis; Bioinformatics; Biology; Biomarkers, Tumor - genetics; Bladder; Bladder cancer; Bufeta; Cancer; Cancer genetics; Cancer research; Case-Control Studies; Cell cycle; Complexity; Càncer; Data mining; Disease susceptibility; Efectes fisiològics; Environmental risk; Epidemiology; Female; Follow-Up Studies; Gene expression; Genes; Genetic Predisposition to Disease; Genetics; Genomes; Health aspects; Health risks; Hospitals; Humans; Identification methods; Inflammation; Inflammation - genetics; Inflammation Mediators - analysis; Learning algorithms; Machine learning; Male; Mathematics; Medical research; Medicine; Methods; Middle Aged; Polymorphism, Single Nucleotide - genetics; Prognosis; Regression analysis; Risk Factors; Single nucleotide polymorphisms; Single-nucleotide polymorphism; Smoking; Smoking - adverse effects; Smoking - genetics; Studies; Tabac; Texas; Tobacco; Tumors; Urinary bladder; Urinary Bladder Neoplasms - etiology; Young Adult; Texas; United States--US; Maryland; Spain