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Saba, Karim;Wettstein, Marian S.;Lieger, Laura;Hötker, Andreas M.;Donati, Olivio F.;Moch, Holger;Ankerst, Donna P.;Poyet, Cédric;Sulser, Tullio;Eberli, Daniel;Mortezavi, Ashkan
External Validation and Comparison of Prostate Cancer Risk Calculators Incorporating Multiparametric Magnetic Resonance Imaging for Prediction of Clinically Significant Prostate Cancer
Journal of Urology
2020
203
4
719-726
Littmann, Maria;Selig, Katharina;Cohen-Lavi, Liel;Frank, Yotam;Hönigschmid, Peter;Kataka, Evans;Mösch, Anja;Qian, Kun;Ron, Avihai;Schmid, Sebastian;Sorbie, Adam;Szlak, Liran;Dagan-Wiener, Ayana;Ben-Tal, Nir;Niv, Masha Y.;Razansky, Daniel;Schuller, Björn W.;Ankerst, Donna;Hertz, Tomer;Rost, Burkhard
Validity of machine learning in biology and medicine increased through collaborations across fields of expertise
Nature Machine Intelligence
2020
2
1
18-24
Schmidt, Melissa;Ankerst, Donna P.;Chen, Yiyao;Wiethaler, Maria;Slotta-Huspenina, Julia;Becker, Karl-Friedrich;Horstmann, Julia;Kohlmayer, Florian;Lehmann, Andreas;Linkohr, Birgit;Strauch, Konstantin;Schmid, Roland M.;Quante, Anne S.;Quante, Michael
Epidemiologic Risk Factors in a Comparison of a Barrett Esophagus Registry (BarrettNET) and a Case–Control Population in Germany
Cancer Prevention Research
2020
13
4
377-384
Kaissis, Georgios A.;Lohöfer, Fabian K.;Ziegelmayer, Sebastian;Danner, Julia;Jäger, Carsten;Schirren, Rebekka;Ankerst, Donna;Ceyhan, Güralp O.;Friess, Helmut;Rummeny, Ernst J.;Weichert, Wilko;Braren, Rickmer F.
Borderline-resectable pancreatic adenocarcinoma: Contour irregularity of the venous confluence in pre-operative computed tomography predicts histopathological infiltration
PLOS ONE
2019
14
1
e0208717
Hoffmann, D;Thurner, S;Ankerst, D;Damme, K;Windisch, W;Brugger, D
Chickens’ growth performance and pancreas development exposed to soy cake varying in trypsin inhibitor activity, heat-degraded lysine concentration, and protein solubility in potassium hydroxide
Poultry Science
2019
98
6
2489-2499
Krautenbacher, Norbert;Flach, Nicolai;Böck, Andreas;Laubhahn, Kristina;Laimighofer, Michael;Theis, Fabian J.;Ankerst, Donna P.;Fuchs, Christiane;Schaub, Bianca
A strategy for high‐dimensional multivariable analysis classifies childhood asthma phenotypes from genetic, immunological, and environmental factors
Allergy
2019
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.
Multi-cohort modeling strategies for scalable globally accessible prostate cancer risk tools
BMC Medical Research Methodology
2019
19
1
Kaissis, Georgios;Ziegelmayer, Sebastian;Lohöfer, Fabian;Algül, Hana;Eiber, Matthias;Weichert, Wilko;Schmid, Roland;Friess, Helmut;Rummeny, Ernst;Ankerst, Donna;Siveke, Jens;Braren, Rickmer
A machine learning model for the prediction of survival and tumor subtype in pancreatic ductal adenocarcinoma from preoperative diffusion-weighted imaging
European Radiology Experimental
2019
3
1
Höfler, Josef
Statistical modeling with finite mixtures of skew-t distributions and their application in the life sciences
2020
Dissertation
143 p.
Grill, Sonja;Ankerst, Donna P.;Gail, Mitchell H.;Chatterjee, Nilanjan;Pfeiffer, Ruth M.
Comparison of approaches for incorporating new information into existing risk prediction models
Statistics in Medicine
2016
36
7
1134-1156
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