ReviewThe Urologic clinics of North America2022
Artificial Intelligence Applications in Urology: Reporting Standards to Achieve Fluency for Urologists.
Review in The Urologic clinics of North America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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
11 citing papers in PubMed.
- Development and validation of an interpretable prediction model for high-grade vesicoureteral reflux in children with urinary tract infections.Frontiers in medicine · 2026Article
- Urological diagnostics based on kidney stone detection in CT imaging using YOLOv8 deep learning framework.Frontiers in medicine · 2026Article
- Current and Future Applications of Artificial Intelligence to Diagnose and Treat Male Infertility.Advances in experimental medicine and biology · 2025Review
- ChatGPT and generative AI in urology and surgery-A narrative review.BJUI compass · 2024Review
- Bioinformatics in urology - molecular characterization of pathophysiology and response to treatment.Nature reviews. Urology · 2024Review
- Artificial intelligence and urology: ethical considerations for urologists and patients.Nature reviews. Urology · 2024Review
- CT Rendering and Radiomic Analysis in Post-Chemotherapy Retroperitoneal Lymph Node Dissection for Testicular Cancer to Anticipate Difficulties for Young Surgeons.Journal of imaging · 2023Article
- Automated Capture of Intraoperative Adverse Events Using Artificial Intelligence: A Systematic Review and Meta-Analysis.Journal of clinical medicine · 2023Review
- Is Artificial Intelligence Replacing Our Radiology Stars? Not Yet!European urology open science · 2023Article
- An update on computational pathology tools for genitourinary pathology practice: A review paper from the Genitourinary Pathology Society (GUPS).Journal of pathology informatics · 2023Review
- Surgical gestures as a method to quantify surgical performance and predict patient outcomes.NPJ digital medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
The growth and adoption of artificial intelligence has led to impressive results in urology. As artificial intelligence grows more ubiquitous, it is important to establish artificial intelligence literacy in the workforce. To this end, we present a narrative review of the literature of artificial intelligence and machine learning in urology and propose a checklist of reporting standards to improve readability and evaluate the current state of the literature. The listed article demonstrated heterogeneous reporting of methodologies and outcomes, limiting generalizability of research. We hope that this review serves as a foundation for future evaluation of medical research in artificial intelligence.
Indexed as
Identifiers
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.