ReviewProstate international2025
Artificial intelligence-driven digital pathology in urological cancers: current trends and future directions.
Review in Prostate international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Patients with high-risk features on active surveillance for prostate cancer.Prostate international · 2026Review
- Intravesical gemcitabine versus Bacillus Calmette-Guérin (BCG) for intermediate-/high-risk non-muscle-invasive bladder cancer during the BCG shortage: Safety, efficacy, and health-economic context.Investigative and clinical urology · 2026Observational
- Plasma circulating tumor deoxyribonucleic acid methylation enables noninvasive disease stratification beyond prostate-specific antigen in prostate cancer.Prostate international · 2026Article
- Association of initial transurethral resection staging on survival in radical cystectomy patients.Investigative and clinical urology · 2026Article
- Benchmarking multiple instance learning architectures from patches to pathology for prostate cancer detection and grading using attention-based weak supervision.Scientific reports · 2026Article
- Artificial intelligence in genitourinary pathology.Histopathology · 2026Review
- Artificial intelligence-based personalized oncological outcome prediction model for upper urinary tract urothelial carcinoma after radical nephroureterectomy: A development and multicenter validation.Investigative and clinical urology · 2026Article
- Treatment strategies for cisplatin-ineligible metastatic bladder cancer: Emerging therapies and future perspectives.Investigative and clinical urology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) in digital pathology has gained attention owing to its potential in urological cancer diagnosis and management. This review highlights AI's applications and challenges in three major urological cancers. Prostate cancer studies have demonstrated reliable diagnostic performance and promising prognosis prediction. Renal cancer study shows potential but faces challenges in generalizability and prognosis. Bladder cancer studies are limited by the lack of large-scale datasets. Despite of these active studies, challenges remain regarding data availability, prognosis, and generalizability. Future efforts should emphasize multimodal approaches and multi-institutional collaboration with larger datasets to fully realize the potential of AI in urological cancers.
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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.