ArticleCommunications medicine2021
Predicting prostate cancer specific-mortality with artificial intelligence-based Gleason grading.
Article in Communications medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 47 citations in OpenAlex.
- HistoEncoder: A digital pathology foundation model for prostate cancer.Journal of pathology informatics · 2026Article
- Immune Spatial Organization Predicts Distant Metastasis Risk in Aggressive Localized Prostate Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026Article
- The state of the art in artificial intelligence and digital pathology in prostate cancer.Nature reviews. Urology · 2026Review
- Longitudinal outcome prediction of prostate cancer patients on active surveillance using multiple instance learning.Journal of medical imaging (Bellingham, Wash.) · 2025Article
- Artificial intelligence-assisted prostate cancer diagnosis for reduced use of immunohistochemistry.Communications medicine · 2025Article
- Computational Morphological Assessment of Bladder Cancer Tissue Is Prognostic of Recurrence and Overall Survival Following Transurethral Resection.JCO clinical cancer informatics · 2025Article
- Clinical implications of deep learning based image analysis of whole radical prostatectomy specimens.Scientific reports · 2025Article
- Do explainable AI (XAI) methods improve the acceptance of AI in clinical practice? An evaluation of XAI methods on Gleason grading.The journal of pathology. Clinical research · 2025Article
- A selective CutMix approach improves generalizability of deep learning-based grading and risk assessment of prostate cancer.Journal of pathology informatics · 2024Article
- Prostate Cancer Risk Stratification by Digital Histopathology and Deep Learning.JCO clinical cancer informatics · 2024Article
- Harnessing artificial intelligence for prostate cancer management.Cell reports. Medicine · 2024Review
- Artificial intelligence unravels interpretable malignancy grades of prostate cancer on histology images.Npj imaging · 2024Article
- Application of artificial intelligence in the diagnosis and treatment of urinary tumors.Frontiers in oncology · 2024Review
- Artificial intelligence in pathologic diagnosis, prognosis and prediction of prostate cancer.American journal of clinical and experimental urology · 2024Review
- Biomarkers in Cancer Detection, Diagnosis, and Prognosis.Sensors (Basel, Switzerland) · 2023Review
- Humans inherit artificial intelligence biases.Scientific reports · 2023Article
- Privacy risks of whole-slide image sharing in digital pathology.Nature communications · 2023Article
- Deep learning models for histologic grading of breast cancer and association with disease prognosis.NPJ breast cancer · 2022Article
- The Cellular and Molecular Immunotherapy in Prostate Cancer.Vaccines · 2022Review
- Prostate Cancer Risk Stratification via Nondestructive 3D Pathology with Deep Learning-Assisted Gland Analysis.Cancer research · 2022Article
Corrections and comments
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Authors and funding
23 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Gleason grading of prostate cancer is an important prognostic factor, but suffers from poor reproducibility, particularly among non-subspecialist pathologists. Although artificial intelligence (A.I.) tools have demonstrated Gleason grading on-par with expert pathologists, it remains an open question whether and to what extent A.I. grading translates to better prognostication. Methods: In this study, we developed a system to predict prostate cancer-specific mortality via A.I.-based Gleason grading and subsequently evaluated its ability to risk-stratify patients on an independent retrospective cohort of 2807 prostatectomy cases from a single European center with 5-25 years of follow-up (median: 13, interquartile range 9-17). Results: Here, we show that the A.I.'s risk scores produced a Conclusions: Our results suggest that A.I.-based Gleason grading can lead to effective risk stratification, and warrants further evaluation for improving disease management.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.