ArticleInternational neurourology journal2022
Development of an Artificial Intelligence-Based Support Technology for Urethral and Ureteral Stricture Surgery.
Article in International neurourology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 11 citations in OpenAlex.
- 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
- From Machine Learning to Generative Artificial Intelligence in Urology: Technological Evolution and Future Perspectives.International neurourology journal · 2026Review
- Impact of Simulated Radiation Dose Reduction on Deep Learning-Based Renal Segmentation Performance: A Simulation Study Using the KiTS21 (2021 Kidney and Kidney Tumor Segmentation Challenge) Dataset.International neurourology journal · 2026Article
- Current advances in the use of artificial intelligence in predicting and managing urological complications.International urology and nephrology · 2024Review
- Machine learning algorithm predicts urethral stricture following transurethral prostate resection.World journal of urology · 2024Article
- Advances in urethral stricture diagnostics and urethral reconstruction beyond traditional imaging: a scoping review.Central European journal of urology · 2024Review
- Artificial Intelligence in Andrology: From Semen Analysis to Image Diagnostics.The world journal of men's health · 2024Review
- The Current State of Artificial Intelligence Application in Urology.International neurourology journal · 2023Article
- General Overview of Artificial Intelligence for Interstitial Cystitis in Urology.International neurourology journal · 2023Article
- New Trends in Innovative Technologies Applying Artificial Intelligence to Urinary Diseases.International neurourology journal · 2022Article
- An Artificial Intelligence-assisted Diagnostic System Improves Upper Urine Tract Cytology Diagnosis.In vivo (Athens, Greece)Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
purposeThis paper proposes a technological system that uses artificial intelligence to recognize and guide the operator to the exact stenosis area during endoscopic surgery in patients with urethral or ureteral strictures. The aim of this technological solution was to increase surgical efficiency.
methodsThe proposed system utilizes the ResNet-50 algorithm, an artificial intelligence technology, and analyzes images entering the endoscope during surgery to detect the stenosis location accurately and provide intraoperative clinical assistance. The ResNet-50 algorithm was chosen to facilitate accurate detection of the stenosis site.
resultsThe high recognition accuracy of the system was confirmed by an average final sensitivity value of 0.96. Since sensitivity is a measure of the probability of a true-positive test, this finding confirms that the system provided accurate guidance to the stenosis area when used for support in actual surgery.
conclusionThe proposed method supports surgery for patients with urethral or ureteral strictures by applying the ResNet-50 algorithm. The system analyzes images entering the endoscope during surgery and accurately detects stenosis, thereby assisting in surgery. In future research, we intend to provide both conservative and flexible boundaries of the strictures.
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Registered trials
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