Zobrazeno 1 - 10
of 57
pro vyhledávání: '"Henning Cammann"'
Autor:
Xin-Hai Hu, Henning Cammann, Hellmuth-A Meyer, Klaus Jung, Hong-Biao Lu, Natalia Leva, Ahmed Magheli, Carsten Stephan, Jonas Busch
Publikováno v:
Asian Journal of Andrology, Vol 16, Iss 6, Pp 897-901 (2014)
Many computer models for predicting the risk of prostate cancer have been developed including for prediction of biochemical recurrence (BCR). However, models for individual BCR free probability at individual time-points after a BCR free period are ra
Externí odkaz:
https://doaj.org/article/5b5c2620a8fd438388ef7d2a5db63982
Publikováno v:
Nature Reviews Urology. 10:174-182
Artificial neural networks (ANNs) are mathematical models that are based on biological neural networks and are composed of interconnected groups of artificial neurons. ANNs are used to map and predict outcomes in complex relationships between given '
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::18ae48232d7d649440ba88ddb7ce37fd
https://doi.org/10.1038/nrurol.2013.9
https://doi.org/10.1038/nrurol.2013.9
Publikováno v:
EJIFCC
PSA screening reduces PCa-mortality but the disadvantages overdiagnosis and overtreatment require multivariable risk-prediction tools to select appropriate treatment or active surveillance. This review explains the differences between the two largest
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::6468034f8a7e1605a2384f8d5815de3d
https://pubmed.ncbi.nlm.nih.gov/27683457
https://pubmed.ncbi.nlm.nih.gov/27683457
Autor:
Kurt Miller, Henning Cammann, Holger Gerullis, Thorsten H. Ecke, Stefan Koch, Jürgen Ruttloff, Steffen Hallmann, Carsten Stephan
Publikováno v:
ISRN Urology
Background. Multivariate models are used to increase prostate cancer (PCa) detection rate and to reduce unnecessary biopsies. An external validation of the artificial neural network (ANN) “ProstataClass” (ANN-Charité) was performed with daily ro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::74ab545c218de5688b96d3a54d8d7ef9
https://doi.org/10.5402/2012/643181
https://doi.org/10.5402/2012/643181
Autor:
Henning Cammann, Hellmuth-A. Meyer, Carsten Stephan, Michael Lein, Kurt Miller, Martin Bender, Klaus Jung
Publikováno v:
International Journal of Urology. 17:62-68
Objectives: To carry out an internal validation of the retrospectively trained artificial neural network (ANN) ‘ProstataClass’. Methods: A prospectively collected database of 393 patients undergoing 8–12 core prostate biopsy was analyzed. Data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4760ebb83ddc5ab4041e73cfc47e5d91
https://doi.org/10.1111/j.1442-2042.2009.02417.x
https://doi.org/10.1111/j.1442-2042.2009.02417.x
Autor:
Klaus Jung, Kurt Miller, Henning Cammann, Anna-Maria Kahrs, Mark Schrader, Michael Lein, Serdar Deger, Carsten Stephan
Publikováno v:
The Prostate. 69:198-207
Background The aim of this study was to combine the new automated Access [-2]proPSA (p2PSA) assay with a percent free PSA (%fPSA) based artificial neural network (ANN) or logistic regression (LR) model to enhance discrimination between patients with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d3ef0c24db2a82141266b9036c84b821
https://doi.org/10.1002/pros.20872
https://doi.org/10.1002/pros.20872
Autor:
Anne Rüggeberg, Robert M. Eisele, Andreas Lun, Sebastian Pawellek, Andreas Weimann, Cornelia Radke, Christian W. Müller, Ulrich Sack, Jochen Klupp, Henning Cammann, Michael Hippler-Benscheid
Publikováno v:
LaboratoriumsMedizin. 32:148-157
Background: T-cell activation markers in peripheral blood are helpful to detect acute rejection in liver transplantation (LTX) patients with immunosuppression by Cyclosporin A or Tacrolimus. Immunosuppression including basiliximab may influence the d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dc6874e80fccc8e81ed0dbb72fc73aed
https://doi.org/10.1515/jlm.2008.031
https://doi.org/10.1515/jlm.2008.031
Autor:
Michael Lein, Klaus Jung, Carsten Stephan, Patrik Finne, Chuanliang Xu, Henning Cammann, Hellmuth-Alexander Meyer, Ulf-Håkan Stenman
Publikováno v:
University of Helsinki
OBJECTIVES Different artificial neural networks (ANNs) using total prostate-specific antigen (PSA) and percentage of free PSA (%fPSA) have been introduced to enhance the specificity of prostate cancer detection. The applicability of independently tra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::16674dbfe299934ff157f940cf6fa9b7
https://doi.org/10.1016/j.urology.2007.04.004
https://doi.org/10.1016/j.urology.2007.04.004
Autor:
Hartwig Huland, Patrik Finne, Mark F. Wildhagen, Bob Djavan, Carsten Stephan, Bert G. Blijenberg, Markus Graefen, Axel Semjonow, Chuanliang Xu, Hellmuth-Alexander Meyer, Alexander Haese, Henning Cammann, Klaus Jung, Eleftherios P. Diamandis, Ulf-Håkan Stenman, Mesut Remzi
Publikováno v:
World Journal of Urology, 25(1), 95-103. Springer-Verlag
Use of percent free PSA (%fPSA) and artificial neural networks (ANNs) can eliminate unnecessary prostate biopsies. In a total of 4,480 patients from five centers with PSA concentrations in the range of 2-10 ng/ml an IMMULITE PSA-based ANN (iANN) was
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5dcc941135f39d2aa0c5d281b60afec6
https://doi.org/10.1007/s00345-006-0132-9
https://doi.org/10.1007/s00345-006-0132-9
Autor:
Carsten Stephan, Alain Houlgatte, Sébastien Vincendeau, Axel Semjonow, Martin Boegemann, Jean-Sebastien Blanchet, Klaus Jung, Henning Cammann
Publikováno v:
BJU international. 117(1)
Objectives To prospectively test the diagnostic accuracy of the percentage of prostate specific antigen (PSA) isoform [–2]proPSA (%p2PSA) and the Prostate Health Index (PHI), and to determine their role for discrimination between significant and in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c41d9a89abb8390e9619d1f287feff46
https://pubmed.ncbi.nlm.nih.gov/26676682
https://pubmed.ncbi.nlm.nih.gov/26676682