Trends of ‘Artificial Intelligence, Machine Learning, Virtual Reality and Radiomics in Urolithiasis’ over the last 30 years (1994–2023) as published in the literature (PubMed): a Comprehensive review.

Review Urology & Nephrology

Advances in percutaneous renal puncture: a comprehensive review of the literature

Vasileios Tatanis et al.

Summary: This review discusses the advances in percutaneous renal puncture. The use of specific agents can improve ultrasonic guidance, making the challenging step of gaining access to the kidney easier for the experienced surgeon and more accessible for the resident urologist. Future developments in electromagnetic and three-dimensional technology may establish a high level of accuracy with decreased rates of related complications, even in the hands of beginners.

CURRENT OPINION IN UROLOGY (2023)

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Review Urology & Nephrology

Transforming urinary stone disease management by artificial intelligence-based methods: A comprehensive review

Anastasios Anastasiadis et al.

Summary: This article aims to provide a comprehensive review of the application of artificial intelligence (AI) in the assessment and management of urinary stone disease. The review found that AI has a wide range of potential applications in improving various medical procedures related to stone disease, including diagnosis, prediction of treatment outcomes, optimization of surgical procedures, and elucidation of stone chemistry. However, more high-quality studies are needed to establish the integration of AI in the management of urinary stone disease.

ASIAN JOURNAL OF UROLOGY (2023)

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Article Urology & Nephrology

Evaluation and understanding of automated urinary stone recognition methods

Jonathan El Beze et al.

Summary: This study evaluates the potential of automated machine-learning methods for recognizing urinary stones in endoscopy. Shallow classification methods and deep-learning-based methods achieved relatively high sensitivity, specificity, and positive predictive value for stone recognition when using surface and section images. Further studies on a larger panel of stones are needed to develop these methods.

BJU INTERNATIONAL (2022)

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Article Urology & Nephrology

Machine Learning-Assisted Preoperative Diagnosis of Infection Stones in Urolithiasis Patients

TingTing Chen et al.

Summary: This study developed machine learning models for preoperative identification of infection stones in urolithiasis patients. Among the five ML models tested, the RFC model demonstrated superior discrimination and outperformed the traditional LR model. Gender, urine white blood cell counts, and urine pH level were the top three important features in the prediction of infection stones.

JOURNAL OF ENDOUROLOGY (2022)

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Article Urology & Nephrology

Validity of a patient-specific percutaneous nephrolithotomy (PCNL) simulated surgical rehearsal platform: impact on patient and surgical outcomes

Ahmed Ghazi et al.

Summary: The study evaluated the impact of high-fidelity patient-specific simulations on surgical outcomes in percutaneous nephrolithotomy procedures. Results showed significant improvements in fluoroscopy time, percutaneous needle access attempts, complications, and additional procedures in the rehearsal group compared to the standard group, demonstrating the effectiveness of patient-specific procedural rehearsal in enhancing surgical performance and patient outcomes.

WORLD JOURNAL OF UROLOGY (2022)

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Article Urology & Nephrology

How specific are patient-specific simulations? Analyzing the accuracy of 3D-printing and modeling to create patient-specific rehearsals for complex urological procedures

Rachel Melnyk et al.

Summary: This study utilized 3D printing and molding to develop hydrogel models for surgical rehearsals, with three methods employed to evaluate their anatomical accuracy. The results demonstrated high similarity in geometry and alignment between the models and actual patient anatomy, supporting the use of anatomically accurate surgical rehearsals.

WORLD JOURNAL OF UROLOGY (2022)

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Article Medicine, Research & Experimental

Changing trends in clinical research literature on PubMed database from 1991 to 2020

Xiyi Zhao et al.

Summary: This study analyzed the type and quantity of clinical research publications in the PubMed database over three decades. The results showed significant changes in the composition and number of clinical studies. Case report/series, case control study, and narrative review decreased, while cohort study, cross-sectional study, systematic reviews, and systematic review and meta-analysis literature increased.

EUROPEAN JOURNAL OF MEDICAL RESEARCH (2022)

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Article Urology & Nephrology

Application of Artificial Intelligence-Based Classifiers to Predict the Outcome Measures and Stone-Free Status Following Percutaneous Nephrolithotomy for Staghorn Calculi: Cross-Validation of Data and Estimation of Accuracy

B. M. Zeeshan Hameed et al.

Summary: The study developed a decision support system for predicting the postoperative outcome of kidney stone treatment procedures, particularly PCNL, with high accuracy. By using machine learning techniques and a multi-classifier scheme, the system could effectively predict the stone-free rate by extracting specific features and analyzing data.

JOURNAL OF ENDOUROLOGY (2021)

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Review Medicine, General & Internal

Artificial Intelligence and Its Impact on Urological Diseases and Management: A Comprehensive Review of the Literature

B. M. Zeeshan Hameed et al.

Summary: Artificial intelligence has been widely adopted in urology to detect, treat, and estimate the outcomes of urological diseases, providing advantages over traditional methods.

JOURNAL OF CLINICAL MEDICINE (2021)

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Review Urology & Nephrology