Datenbasierte Ansätze für moderne klinische Risikovorhersagen

Autor: Tolksdorf, Johanna Elisabeth

In this thesis the use of data scientific approaches in the life sciences is illustrated by means of contemporary prostate cancer risk models. Validation techniques are introduced and analytical confidence intervals for selected methods derived. In a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______518::375b244534b3f916bbf0d7e0c0f759d2
https://mediatum.ub.tum.de/1487626

Multi-cohort modeling strategies for scalable globally accessible prostate cancer risk tools

Autor: Tolksdorf, Johanna, Kattan, Michael W, Boorjian, Stephen A, Freedland, Stephen J, Saba, Karim, Poyet, Cedric, Guerrios, Lourdes, De Hoedt, Amanda, Liss, Michael A, Leach, Robin J, Hernandez, Javier, Vertosick, Emily, Vickers, Andrew J, Ankerst, Donna P

Publikováno v: BMC Medical Research Methodology, Vol 19, Iss 1, Pp 1-11 (2019)
BMC Medical Research Methodology

Background Online clinical risk prediction tools built on data from multiple cohorts are increasingly being utilized for contemporary doctor-patient decision-making and validation. This report outlines a comprehensive data science strategy for buildi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::15312329da300c9b00cbe51308b93bdc
https://www.zora.uzh.ch/id/eprint/215161/

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Multi-cohort modeling strategies for scalable globally accessible prostate cancer risk tools.

Autor: Tolksdorf J; Departments of Mathematics and Life Sciences, Technical University of Munich, Boltzmannstr.3, 85747, Garching near Munich, Germany., Kattan MW; Department of Quantitative Health Sciences, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH, 44195, USA., Boorjian SA; Department of Urology, Mayo Clinic, 200 1st St SW W4, Rochester, MN, 55905, USA., Freedland SJ; Department of Urology, Durham Veterans Administration Medical Center, 508 Fulton St, Durham, NC, 27705, USA.; Department of Surgery, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Los Angeles, CA, 90048, USA., Saba K; Department of Urology, University Hospital Zurich, University of Zurich, Rämistrasse 71, CH-8006, Zurich, Switzerland., Poyet C; Department of Urology, University Hospital Zurich, University of Zurich, Rämistrasse 71, CH-8006, Zurich, Switzerland., Guerrios L; Department of Surgery, Urology Section, Veterans Affairs Caribbean Healthcare System, 10 Calle Casia, San Juan, 00921-3201, Puerto Rico., De Hoedt A; Department of Urology, Durham Veterans Administration Medical Center, 508 Fulton St, Durham, NC, 27705, USA., Liss MA; Department of Urology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229, USA., Leach RJ; Department of Urology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229, USA., Hernandez J; Department of Urology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229, USA., Vertosick E; Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA., Vickers AJ; Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA., Ankerst DP; Departments of Mathematics and Life Sciences, Technical University of Munich, Boltzmannstr.3, 85747, Garching near Munich, Germany. ankerst@tum.de.

Publikováno v: BMC medical research methodology [BMC Med Res Methodol] 2019 Oct 15; Vol. 19 (1), pp. 191. Date of Electronic Publication: 2019 Oct 15.