Evaluation of automatic discrimination between benign and malignant prostate tissue in the era of high precision digital pathology

BMC Bioinformatics

Research

Thomas J. Vogl¹  Benedikt Höh²  Philipp Mandel²  Mike Wenzel²  Katrin Bankov³  Jens Köllermann³  Claudia Döring³  Henning Reis³  Nadine Flinner³  Simon Bernatz⁴  Peter J. Wild⁵  Yauheniya Zhdanovich⁶  Jörg Ackermann⁷  Ina Koch⁷  Patrick Harter⁸  Katharina Filipski⁹ 

[1] Department of Diagnostic and Interventional Radiology, Goethe University Frankfurt am Main, University Hospital Frankfurt, 60590, Frankfurt, Germany;Department of Urology, Goethe University Frankfurt am Main, University Hospital Frankfurt, 60590, Frankfurt, Germany;Dr. Senckenberg Institute for Pathology, Goethe University Frankfurt am Main, University Hospital Frankfurt, 60590, Frankfurt, Germany;Dr. Senckenberg Institute for Pathology, Goethe University Frankfurt am Main, University Hospital Frankfurt, 60590, Frankfurt, Germany;Department of Diagnostic and Interventional Radiology, Goethe University Frankfurt am Main, University Hospital Frankfurt, 60590, Frankfurt, Germany;Frankfurt Cancer Institute (FCI), University Hospital Frankfurt, 60590, Frankfurt, Germany;Dr. Senckenberg Institute for Pathology, Goethe University Frankfurt am Main, University Hospital Frankfurt, 60590, Frankfurt, Germany;Wildlab, University Hospital Frankfurt MVZ GmbH, 60590, Frankfurt, Germany;Frankfurt Institute for Advanced Studies (FIAS), 60438, Frankfurt, Germany;Institute of Pathology, Ludwig-Maximilians University Munich, Thalkirchner Str. 36, 80337, Munich, Germany;Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, 10117, Berlin, Germany;Molecular Bioinformatics Group, Institute of Computer Science, Faculty of Computer Science and Mathematics, Robert-Mayer-Straße 11-15, 60325, Frankfurt, Germany;Neurological Institute (Edinger Institute), University Hospital Frankfurt, 60590, Frankfurt, Germany;Neurological Institute (Edinger Institute), University Hospital Frankfurt, 60590, Frankfurt, Germany;German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany;University Cancer Center (UCT) Frankfurt, Frankfurt, Germany;Frankfurt Cancer Institute (FCI), University Hospital Frankfurt, 60590, Frankfurt, Germany;

关键词: Prostate cancer;    Prediction;    Quantitative features;    Statistical analysis;    Machine learning;   

DOI  :  10.1186/s12859-022-05124-9

 received in 2022-08-05, accepted in 2022-12-23,  发布年份 2022

来源: Springer

【 授权许可】

CC BY   
© The Author(s) 2023

【 图 表 】

Fig. 3

40798_2022_490_Article_IEq60.gif

Fig. 59

Fig. 3

Fig. 4

Fig. 52

Fig. 11

Fig. 3

Fig. 51

Fig. 9

Fig. 6

Fig. 1

Fig. 8

Fig. 3

Fig. 49

Fig. 4

Fig. 7

Fig. 4

Fig. 6

Fig. 2

Fig. 5

Fig. 1

Fig. 4

Fig. 2

Fig. 5

Fig. 5

41116_2022_35_Article_IEq655.gif

Fig. 47

41116_2022_35_Article_IEq649.gif

41116_2022_35_Article_IEq645.gif

41116_2022_35_Article_IEq639.gif

41116_2022_35_Article_IEq635.gif

Fig. 46

41116_2022_35_Article_IEq632.gif

41116_2022_35_Article_IEq627.gif

41116_2022_35_Article_IEq626.gif

41116_2022_35_Article_IEq624.gif

41116_2022_35_Article_IEq621.gif

Fig. 45

41116_2022_35_Article_IEq599.gif

41116_2022_35_Article_IEq598.gif

41116_2022_35_Article_IEq597.gif

Fig. 44

41116_2022_35_Article_IEq595.gif

Fig. 43

41116_2022_35_Article_IEq593.gif

Fig. 1

41116_2022_35_Article_IEq591.gif

41116_2022_35_Article_IEq590.gif

41116_2022_35_Article_IEq589.gif

41116_2022_35_Article_IEq588.gif

41116_2022_35_Article_IEq587.gif

41116_2022_35_Article_IEq586.gif

41116_2022_35_Article_IEq585.gif

41116_2022_35_Article_IEq584.gif

41116_2022_35_Article_IEq582.gif

41116_2022_35_Article_IEq581.gif

41116_2022_35_Article_IEq579.gif

41116_2022_35_Article_IEq576.gif

41116_2022_35_Article_IEq569.gif