ReviewDiagnostics (Basel, Switzerland)2023
Deep Learning Methodologies Applied to Digital Pathology in Prostate Cancer: A Systematic Review.
Review in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Applications of Artificial Intelligence for Assessing Fall Risk: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Generalizability of a biopsy-trained artificial intelligence algorithm to TURP and HoLEP specimens for detection of incidental prostate adenocarcinoma.Diagnostic pathology · 2026Article
- GrandQC adaptation as an artificial intelligence tool for quantitative artifact detection in hematoxylin and eosin whole-slide images-Simulation of quality control biopsies day.Journal of pathology informatics · 2026Article
- Olfactory Science and Technology in Prostate Cancer Diagnosis: From Invertebrate Models to Artificial Intelligence.Life (Basel, Switzerland) · 2026Review
- Finding Holes: Pathologist-Level Performance Using AI for Cribriform Morphology Detection in Prostate Cancer.European urology open science · 2026Article
- Article
- Tomorrow's patient management: LLMs empowered by external tools.Nature reviews. Urology · 2026Article
- A generalised vision transformer-based self-supervised model for diagnosing and grading prostate cancer using histological images.Prostate cancer and prostatic diseases · 2025Article
- Unveiling key pathomic features for automated diagnosis and Gleason grade estimation in prostate cancer.BMC medical imaging · 2025Article
- Deep Learning Techniques for Prostate Cancer Analysis and Detection: Survey of the State of the Art.Journal of imaging · 2025Review
- Advanced Deep Learning Approaches in Detection Technologies for Comprehensive Breast Cancer Assessment Based on WSIs: A Systematic Literature Review.Diagnostics (Basel, Switzerland) · 2025Review
- Artificial intelligence in the management of prostate cancer.Nature reviews. Urology · 2025Article
- Development of a deep learning system for predicting biochemical recurrence in prostate cancer.BMC cancer · 2025Article
- A Microscope Setup and Methodology for Capturing Hyperspectral and RGB Histopathological Imaging Databases.Sensors (Basel, Switzerland) · 2024Article
- Clinical Use of Molecular Biomarkers in Canine and Feline Oncology: Current and Future.Veterinary sciences · 2024Review
- Using digital pathology to analyze the murine cerebrovasculature.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2024Article
- Using multi-label ensemble CNN classifiers to mitigate labelling inconsistencies in patch-level Gleason grading.PloS one · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Deep learning (DL), often called artificial intelligence (AI), has been increasingly used in Pathology thanks to the use of scanners to digitize slides which allow us to visualize them on monitors and process them with AI algorithms. Many articles have focused on DL applied to prostate cancer (PCa). This systematic review explains the DL applications and their performances for PCa in digital pathology. Article research was performed using PubMed and Embase to collect relevant articles. A Risk of Bias (RoB) was assessed with an adaptation of the QUADAS-2 tool. Out of the 77 included studies, eight focused on pre-processing tasks such as quality assessment or staining normalization. Most articles (
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What OpenQuestion holds
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.