ReviewInvestigative and clinical urology2024
Applications of artificial intelligence in urologic oncology.
Review in Investigative and clinical urology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 3 of them syntheses that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Artificial intelligence in genitourinary oncology: publication trends and systematic review.BJU international · 2026Pooled it
- Application Value of Radiomics-Based Machine Learning for Preoperative Risk Stratification of Bladder Cancer: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Algorithms on the rise: a machine learning-driven survey of prostate cancer literature.Frontiers in oncology · 2025Pooled it
- Article
- Advancing Genitourinary Cancer Surgery: The Role of Artificial Intelligence and Robotics.Journal of clinical medicine · 2026Review
- The role of artificial intelligence in advancing urologic care: From diagnostics to therapeutics.Surgery in practice and science · 2026Review
- External validation of the cancer of the prostate risk assessment score to predict treatment failure after high-intensity focused ultrasound.Prostate international · 2026Article
- Artificial intelligence in urological malignancy diagnosis and prognosis: current status and future prospects.The Canadian journal of urology · 2026Review
- Multimodal artificial intelligence in urologic precision oncology: from algorithm to translational medicine (a systemized narrative review).Frontiers in oncology · 2026Review
- Predicting recurrence of prostate cancer after radical treatment using AI models based on PET/CT radiomics: a dual-center study.Frontiers in oncology · 2026Article
- Multimodality focal therapy for prostate cancer: outcome of theProstate international · 2025Article
- Artificial intelligence-driven digital pathology in urological cancers: current trends and future directions.Prostate international · 2025Review
- Exploring patient and clinician opinions, perspectives and acceptance of the use of artificial intelligence in the histological diagnosis of prostate cancer.BJUI compass · 2025Article
- Revisiting angiomyolipomas: The significance of a rich blood supply on imaging for risk-adapted decision making.Investigative and clinical urology · 2025Article
- Inverted Urothelial Papilloma in a Young Woman: A Case Report and Review of Diagnostic Advances.Cureus · 2025Article
- Assessment of artificial intelligence performance in answering questions on onabotulinum toxin and sacral neuromodulation.Investigative and clinical urology · 2025Article
- Multimodal prognostic models for bladder urothelial carcinoma: uroplakin III combined with serum and demographic data.Frontiers in oncology · 2025Article
- A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.Frontiers in medicine · 2025Article
- Deep learning in renal ultrasound: applications, challenges, and future outlook.Frontiers in oncology · 2025Review
- Artificial Intelligence-Based Classification and Segmentation of Bladder Cancer in Cystoscope Images.Cancers · 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
6 authors.
Funding
Abstract
purposeWith the recent rising interest in artificial intelligence (AI) in medicine, many studies have explored the potential and usefulness of AI in urological diseases. This study aimed to comprehensively review recent applications of AI in urologic oncology. MATERIALS AND
methodsWe searched the PubMed-MEDLINE databases for articles in English on machine learning (ML) and deep learning (DL) models related to general surgery and prostate, bladder, and kidney cancer. The search terms were a combination of keywords, including both "urology" and "artificial intelligence" with one of the following: "machine learning," "deep learning," "neural network," "renal cell carcinoma," "kidney cancer," "urothelial carcinoma," "bladder cancer," "prostate cancer," and "robotic surgery."
resultsA total of 58 articles were included. The studies on prostate cancer were related to grade prediction, improved diagnosis, and predicting outcomes and recurrence. The studies on bladder cancer mainly used radiomics to identify aggressive tumors and predict treatment outcomes, recurrence, and survival rates. Most studies on the application of ML and DL in kidney cancer were focused on the differentiation of benign and malignant tumors as well as prediction of their grade and subtype. Most studies suggested that methods using AI may be better than or similar to existing traditional methods.
conclusionsAI technology is actively being investigated in the field of urological cancers as a tool for diagnosis, prediction of prognosis, and decision-making and is expected to be applied in additional clinical areas soon. Despite technological, legal, and ethical concerns, AI will change the landscape of urological cancer 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.