Automated Gleason grading of prostate cancer tissue microarrays via deep learning
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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2045-2322
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
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online resource.
- Erschienen in
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Automated Gleason grading of prostate cancer tissue microarrays via deep learning ; volume:8 ; number:1 ; day:13 ; month:8 ; year:2018 ; pages:1-11 ; date:12.2018
Scientific reports ; 8, Heft 1 (13.8.2018), 1-11, 12.2018
- Urheber
- Beteiligte Personen und Organisationen
-
Fricker, Kim S.
Moret, Michael
Rupp, Niels
Hermanns, Thomas
Fankhauser, Christian
Wey, Norbert
Wild, Peter J.
Rüschoff, Jan H.
Claassen, Manfred
SpringerLink (Online service)
- DOI
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10.1038/s41598-018-30535-1
- URN
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urn:nbn:de:101:1-2018100722564888772021
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:25 MESZ
Datenpartner
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Beteiligte
- Arvaniti, Eirini
- Fricker, Kim S.
- Moret, Michael
- Rupp, Niels
- Hermanns, Thomas
- Fankhauser, Christian
- Wey, Norbert
- Wild, Peter J.
- Rüschoff, Jan H.
- Claassen, Manfred
- SpringerLink (Online service)
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Assessing the performance of deep learning for automated Gleason grading in prostate cancer
Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer
An international multi-institutional validation study of the algorithm for prostate cancer detection and Gleason grading
PCaseek: ultraspecific urinary tumor DNA detection using deep learning for prostate cancer diagnosis and Gleason grading
A comprehensive AI model development framework for consistent Gleason grading
Establishment of a prognostic risk model for prostate cancer based on Gleason grading and cuprotosis related genes
Vergleich der prognostischen Relevanz zwischen dem Gleason-Grading und dem ISUP2014/WHO2016-Grading beim Prostatakarzinom
The value of apparent diffusion coefficient values in predicting Gleason grading of low to intermediate-risk prostate cancer
Carbonic anhydrase IX is a marker of hypoxia and correlates with higher Gleason scores and ISUP grading in prostate cancer
Review by urological pathologists improves the accuracy of Gleason grading by general pathologists
Automated Gleason grading of prostate cancer tissue microarrays via deep learning
Author correction : automated Gleason grading of prostate cancer tissue microarrays via deep learning
Assessing the performance of deep learning for automated Gleason grading in prostate cancer
Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer
An international multi-institutional validation study of the algorithm for prostate cancer detection and Gleason grading
PCaseek: ultraspecific urinary tumor DNA detection using deep learning for prostate cancer diagnosis and Gleason grading
A comprehensive AI model development framework for consistent Gleason grading
Establishment of a prognostic risk model for prostate cancer based on Gleason grading and cuprotosis related genes
Vergleich der prognostischen Relevanz zwischen dem Gleason-Grading und dem ISUP2014/WHO2016-Grading beim Prostatakarzinom
The value of apparent diffusion coefficient values in predicting Gleason grading of low to intermediate-risk prostate cancer
Carbonic anhydrase IX is a marker of hypoxia and correlates with higher Gleason scores and ISUP grading in prostate cancer