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Scandinavian Journal of Urology Volume 48, 2014 - Issue 2
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Original Articles

Interobserver variability in the pathological assessment of radical prostatectomy specimens: Findings of the Laparoscopic Prostatectomy Robot Open (LAPPRO) study

Josefin PerssonDepartment of Urology, Skåne University Hospital, Malmö, Sweden
,
Ulrica WilderängDivision of Clinical Cancer Epidemiology, Department of Oncology, Institute of Clinical Sciences, Sahlgrenska Academy, Gothenburg, Sweden
,
Thomas JibornDepartment of Urology, Skåne University Hospital, Malmö, Sweden
,
Peter N. WiklundDepartment of Molecular Medicine and Surgery, Section of Urology, Karolinska Institutet, Stockholm, Sweden
,
Jan-Erik DamberDepartment of Urology, Institute of Clinical Sciences, Sahlgrenska Academy, Gothenburg, Sweden
,
Jonas HugossonSahlgrenska Academy at Göteborg University, Gothenburg, Sweden
,
Gunnar SteineckDivision of Clinical Cancer Epidemiology, Department of Oncology, Institute of Clinical Sciences, Sahlgrenska Academy, Gothenburg, Sweden; Department of Oncology and Pathology, Section of Clinical Cancer Epidemiology, Karolinska Institutet, Stockholm, Sweden
,
Eva HaglindScandinavian Surgical Outcomes Research Group (SSORG/Göteborg), Department of Surgery, Institution of Clinical Sciences, Sahlgrenska Academy, Gothenburg, Sweden
&
Anders BjartellDepartment of Urology, Skåne University Hospital, Malmö, SwedenCorrespondence[email protected]
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Pages 160-167 | Received 12 Mar 2013, Accepted 20 Jun 2013, Published online: 01 Aug 2013

Citations (15)

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Maryam Derogar, Hanna Dahlstrand, Stefan Carlsson, Anders Bjartell, Jonas Hugosson, Elin Axén, Eva Johansson, Mikael Lagerkvist, Tommy Nyberg, Johan Stranne, Thordis Thorsteinsdottir, Anna Wallerstedt, Eva Haglind, Peter Wiklund & Gunnar Steineck. (2016) Preparedness for side effects and bother in symptomatic men after radical prostatectomy in a prospective, non-randomized trial, LAPPRO. Acta Oncologica 55:12, pages 1467-1476.
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Fredrik Jäderling, Tommy Nyberg, Lennart Blomqvist, Anders Bjartell, Gunnar Steineck & Stefan Carlsson. (2016) Accurate prediction tools in prostate cancer require consistent assessment of included variables. Scandinavian Journal of Urology 50:4, pages 260-266.
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Articles from other publishers (13)

Puria Azadi Moghadam, Ali Bashashati & S. Larry Goldenberg. (2024) Artificial Intelligence and Pathomics. Urologic Clinics of North America 51:1, pages 15-26.
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Anna Hagman, Anna Lantz, Stefan Carlsson, Jonas Höijer, Johan Stranne, S. I. Tyritzis, Eva Haglind, Anders Bjartell, Jonas Hugosson, Olof Akre, Gunnar Steineck & Peter Wiklund. (2021) Urinary continence recovery and oncological outcomes after surgery for prostate cancer analysed by risk category: results from the LAParoscopic prostatectomy robot and open trial. World Journal of Urology 39:9, pages 3239-3249.
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Elin Axén, Rebecka Arnsrud Godtman, Anders Bjartell, Stefan Carlsson, Eva Haglind, Jonas Hugosson, Anna Lantz, Marianne Månsson, Gunnar Steineck, Peter Wiklund & Johan Stranne. (2021) Degree of Preservation of Neurovascular Bundles in Radical Prostatectomy and Recurrence of Prostate Cancer. European Urology Open Science 30, pages 25-33.
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Richard Torres, Eben Olson, Robert HomerDarryl T. Martin, Michael J. LeveneSudhir Perincheri, Preston C. Sprenkle & Peter A. Humphrey. (2021) Initial Evaluation of Rapid, Direct-to-Digital Prostate Biopsy Pathology. Archives of Pathology & Laboratory Medicine 145:5, pages 583-591.
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Dwarikanath Mahapatra, Shiba Kuanar, Behzad Bozorgtabar & Zongyuan Ge. 2021. Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health. Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health 57 67 .
Maximilian E. Tschuchnig, Gertie J. Oostingh & Michael Gadermayr. (2020) Generative Adversarial Networks in Digital Pathology: A Survey on Trends and Future Potential. Patterns 1:6, pages 100089.
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Carrie J. Cai, Samantha Winter, David Steiner, Lauren Wilcox & Michael Terry. (2019) "Hello AI": Uncovering the Onboarding Needs of Medical Practitioners for Human-AI Collaborative Decision-Making. Proceedings of the ACM on Human-Computer Interaction 3:CSCW, pages 1-24.
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Kunal Nagpal, Davis Foote, Yun Liu, Po-Hsuan Cameron Chen, Ellery Wulczyn, Fraser Tan, Niels Olson, Jenny L. Smith, Arash Mohtashamian, James H. Wren, Greg S. Corrado, Robert MacDonald, Lily H. Peng, Mahul B. Amin, Andrew J. Evans, Ankur R. Sangoi, Craig H. Mermel, Jason D. Hipp & Martin C. Stumpe. (2019) Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer. npj Digital Medicine 2:1.
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Ida Arvidsson, Niels Christian Overgaard, Felicia-Elena Marginean, Agnieszka Krzyzanowska, Anders Bjartell, Kalle Astrom & Anders Heyden. (2018) Generalization of prostate cancer classification for multiple sites using deep learning. Generalization of prostate cancer classification for multiple sites using deep learning.
Julie A. Schmidt, Georgina K. Fensom, Sabina Rinaldi, Augustin Scalbert, Paul N. Appleby, David Achaintre, Audrey Gicquiau, Marc J. Gunter, Pietro Ferrari, Rudolf Kaaks, Tilman Kühn, Anna Floegel, Heiner Boeing, Antonia Trichopoulou, Pagona Lagiou, Eleutherios Anifantis, Claudia Agnoli, Domenico Palli, Morena Trevisan, Rosario Tumino, H. Bas Bueno-de-Mesquita, Antonio Agudo, Nerea Larrañaga, Daniel Redondo-Sánchez, Aurelio Barricarte, José Maria Huerta, J. Ramón Quirós, Nick Wareham, Kay-Tee Khaw, Aurora Perez-Cornago, Mattias Johansson, Amanda J. Cross, Konstantinos K. Tsilidis, Elio Riboli, Timothy J. Key & Ruth C. Travis. (2017) Pre-diagnostic metabolite concentrations and prostate cancer risk in 1077 cases and 1077 matched controls in the European Prospective Investigation into Cancer and Nutrition. BMC Medicine 15:1.
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Johan Isaksson, Ida Arvidsson, Kalle Aastrom & Anders Heyden. (2017) Semantic segmentation of microscopic images of H&E stained prostatic tissue using CNN. Semantic segmentation of microscopic images of H&E stained prostatic tissue using CNN.
Anna GummesonIda ArvidssonMattias OhlssonNiels C. OvergaardAgnieszka KrzyzanowskaAnders HeydenAnders BjartellKalle Aström. Automatic Gleason grading of H and E stained microscopic prostate images using deep convolutional neural networks. Automatic Gleason grading of H and E stained microscopic prostate images using deep convolutional neural networks.
Markus Graefen, Thorsten Schlomm, Guido Sauter & Hartwig Huland. (2016) Detailed Quantification of High-grade Cancer Allows Precise Prediction of Prostate Cancer Prognosis. European Urology 69:3, pages 436-437.
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