Percentage Gleason pattern 4 and PI-RADS score predict upgrading in biopsy Grade Group 2 prostate cancer patients without cribriform pattern
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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1433-8726
- Extent
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Online-Ressource
- Language
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Englisch
- Notes
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online resource.
- Bibliographic citation
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Percentage Gleason pattern 4 and PI-RADS score predict upgrading in biopsy Grade Group 2 prostate cancer patients without cribriform pattern ; volume:40 ; number:11 ; day:3 ; month:10 ; year:2022 ; pages:2723-2729 ; date:11.2022
World journal of urology ; 40, Heft 11 (3.10.2022), 2723-2729, 11.2022
- Creator
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Slot, Margaretha A. van der
Seyrek, Neslisah
Kweldam, Charlotte F.
Bakker, Michael A. den
Busstra, Martijn B.
Gan, Melanie
Klaver, Sjoerd
Rietbergen, John B. W.
Leenders, Geert J. L. H. van
- Contributor
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SpringerLink (Online service)
- DOI
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10.1007/s00345-022-04161-6
- URN
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urn:nbn:de:101:1-2023011409212635677506
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:33 AM CEST
Data provider
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Associated
- Slot, Margaretha A. van der
- Seyrek, Neslisah
- Kweldam, Charlotte F.
- Bakker, Michael A. den
- Busstra, Martijn B.
- Gan, Melanie
- Klaver, Sjoerd
- Rietbergen, John B. W.
- Leenders, Geert J. L. H. van
- SpringerLink (Online service)
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Combining weakly and strongly supervised learning improves strong supervision in Gleason pattern classification
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MRI-fusion targeted vs. systematic prostate biopsy - how does the biopsy technique affect Gleason grade concordance and upgrading after radical prostatectomy?
Mri-fusion targeted vs. Systematic prostate biopsy–how does the biopsy technique affect gleason grade concordance and upgrading after radical prostatectomy?
Predicting Gleason sum upgrading from biopsy to radical prostatectomy pathology: a new nomogram and its internal validation
Combining weakly and strongly supervised learning improves strong supervision in Gleason pattern classification
Correlation of MRI-lesion targeted biopsy vs. systematic biopsy gleason score with final pathologicalg gleason score after radical prostatectomy
Deep learning for automatic Gleason pattern classification for grade group determination of prostate biopsies
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Machine learning classifiers can predict Gleason pattern 4 prostate cancer with greater accuracy than experienced radiologists
Percentage fat fraction in magnetic resonance imaging: upgrading the osteoporosis-detecting parameter
Pattern, Poststelle II Pattern bei Mersch
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Quantification of the individual risk of each Gleason pattern, including tertiary Gleason pattern 5, after radical prostatectomy: development of the modified Gleason grade grouping (mGGG) model
MRI-fusion targeted vs. systematic prostate biopsy - how does the biopsy technique affect Gleason grade concordance and upgrading after radical prostatectomy?
Mri-fusion targeted vs. Systematic prostate biopsy–how does the biopsy technique affect gleason grade concordance and upgrading after radical prostatectomy?
Predicting Gleason sum upgrading from biopsy to radical prostatectomy pathology: a new nomogram and its internal validation
Combining weakly and strongly supervised learning improves strong supervision in Gleason pattern classification
Correlation of MRI-lesion targeted biopsy vs. systematic biopsy gleason score with final pathologicalg gleason score after radical prostatectomy
Deep learning for automatic Gleason pattern classification for grade group determination of prostate biopsies
Pattern
Machine learning classifiers can predict Gleason pattern 4 prostate cancer with greater accuracy than experienced radiologists
Percentage fat fraction in magnetic resonance imaging: upgrading the osteoporosis-detecting parameter
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