Tag
Gleason grading
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Sep 6, 2026 Sep 5, 2026 Sep 3, 2026 Sep 2, 2026 Aug 30, 2026 Jan 13, 2022
Apr 9, 2020
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General discussion 2022 thesis · Ch. 6 A look back at the four studies and forward: how AI support fits a pathologist's workflow, and what diagnostics could look like beyond Gleason grading.
AI-assisted Gleason grading 2022 thesis · Ch. 5 Fourteen pathologists graded 160 biopsies with and without AI assistance. With the AI they agreed more with the expert reference, and beat the standalone system.
The PANDA Challenge 2022 thesis · Ch. 4 A global competition on 10,616 public biopsies drew 1,290 developers. The resulting algorithms matched pathologist-level grading on blinded US and EU cohorts.
Automated Gleason grading of prostate biopsies 2022 thesis · Ch. 3 We built a deep-learning system that grades prostate biopsies without manual annotations. It matched the expert consensus and outperformed 10 of 15 pathologists.
General introduction 2022 thesis · Ch. 1 How prostate cancer is diagnosed and graded, why Gleason grading varies so much between pathologists, and what deep learning brings to the problem.
AI for diagnosis of prostate cancer: the PANDA challenge Artificial intelligence (AI) for prostate cancer analysis is ready for clinical implementation, shows a global programming competition, the PANDA challenge.
Improve prostate cancer diagnosis: participate in the PANDA Gleason grading challenge Can you build a deep learning model that can accurately grade prostate biopsies? Participate in the PANDA challenge
The potential of AI in medicine: AI-assistance improves prostate cancer grading In a completely new study we investigated the possible benefits of an AI system for pathologists. Instead of focussing on pathologist-versus-AI, we instead look at potential pathologist-AI synergy.
Pathologist-level Gleason grading using artificial intelligence (AI) & deep learning We developed a fully automated deep learning system to grade prostate biopsies using 5759 biopsies from 1243 patients, and showed that this system achieved pathologist-level performance.