ReviewSurgery in practice and science2026
The role of artificial intelligence in advancing urologic care: From diagnostics to therapeutics.
Review in Surgery in practice and science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence for urodynamic studies: systematic review of methods, performance, and clinical applications.BMC medical informatics and decision making · 2026Pooled it
- Clinical profile and management outcomes of small renal masses: a collaborative multi-institutional Indian study led by the society of genitourinary oncologists.International urology and nephrology · 2026Article
- Artificial Intelligence in the Assessment of Males with Chronic Pelvic Pain Syndrome: An Up-to-Date UPOINTS-Based Narrative Mapping Review.Diagnostics (Basel, Switzerland) · 2026Review
- Impact of Urodynamic Parameters on Treatment Decision-Making in Men Under 50 With Treatment-Resistant Chronic Lower Urinary Tract Symptoms.Neurourology and urodynamics · 2026Article
- Ureteral Orifice Detection in Ureteroscopic Images Based on Large-Kernel Convolutional Neural Networks and Attention-Based Feature Fusion.Bioengineering (Basel, Switzerland) · 2026Article
- Short-term outcomes and surgical technique of cecum and appendix-based urinary diversion in radical cystectomy patients: a case series.International journal of surgery case reports · 2026Article
- Psychometric validation and cross-cultural adaptation of the Persian ICIQ-CLUTS child module for assessing pediatric lower urinary tract symptoms.BMC pediatrics · 2026Article
- Genitourinary symptoms and sexual dysfunction in women with premature ovarian insufficiency: a cross-sectional study with age-comparable controls.Frontiers in endocrinology · 2026Article
- Micro-ultrasound versus mpMRI for targeted prostate biopsy: A systematic review, meta-analysis, and clinical integration.Therapeutic advances in urologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is gradually altering urology by improving diagnostic precision, prognostic evaluation, and therapy decisions in a broad spectrum of urologic diseases. Utilizing machine learning, deep learning, and radiomics, applications of AI have exhibited promise in enhancing cancer identification, stratification, and therapy response prediction, especially in prostate, bladder, and kidney cancers. Beyond cancer therapy, AI enables individually tailored care for benign diseases like benign prostatic hyperplasia, urolithiasis, Functional Urology even in pediatrics by enhancing diagnostic ability and outcome prediction. Heterogeneity of data, model explainability, ethical issues, and lack of prospective validation constrain incorporation into everyday practice. This review summarizes current applications and discusses methodological and ethical limitation, and defines future directions toward enhancing multidisciplinary interaction, standardization across datasets, and prudent implementation. Eventually, AI provides large-scale opportunity to transform urologic care by facilitating individually tailored, expedient, and equitable patient care.
Indexed as
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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.