title: Classification models for early detection of prostate cancer.
abstract: We investigate the performance of different classification models and their ability to recognize prostate cancer in an early stage. We build ensembles of classification models in order to increase the classification performance. We measure the performance of our models in an extensive cross-validation procedure and compare different classification models. The datasets come from clinical examinations and some of the classification models are already in use to support the urologists in their clinical work.
authors.affiliation: Institute of Medical Informatics, Charité - Universitätsmedizin, Hindenburgdamm 30, 12200 Berlin, Germany. joergwichard@web.de
authors.forename: Joerg D
authors.initials: JD
authors.lastname: Wichard
authors.forename: Henning
authors.initials: H
authors.lastname: Cammann
authors.forename: Carsten
authors.initials: C
authors.lastname: Stephan
authors.forename: Thomas
authors.initials: T
authors.lastname: Tolxdorff
mesh_terms: D003627:Data Interpretation, Statistical; D020000:Decision Support Systems, Clinical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D008297:Male; D008954:Models, Biological; D015233:Models, Statistical; D011471:Prostatic Neoplasms / Q000145:classification* / Q000175:diagnosis*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity