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.-Reference-Cited by-同舟云学术

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.

Published:2023-10-26 Issue: Volume: Page:
ISSN:0892-7790
Container-title:Journal of Endourology
language:en
Short-container-title:Journal of Endourology

Author:

Nedbal Carlotta¹,Cerrato Clara¹,Jahrreiss Victoria¹,Pietropaolo Amelia¹,Galosi Andrea Benedetto²³,Castellani Daniele⁴,Somani Bhaskar K¹

Affiliation:

1. University Hospital Southampton NHS Foundation Trust, 7425, Urology, Southampton, United Kingdom of Great Britain and Northern Ireland;

2. Azienda Ospedaliero Universitaria Ospedali Riuniti di Ancona Umberto I G M Lancisi G Salesi, 18494, Urology, Via Conca, Ancona, Marche, Italy, I-60100

3. Polytechnic University of Marche, 9294, Ancona, Italy, 60121;

4. AOU Ospedali Riuniti di Ancona, 18494, via conca 71, Ancona, Italy, 60126;

Publisher

Mary Ann Liebert Inc

Subject

Urology

Link

https://www.liebertpub.com/doi/pdf/10.1089/end.2023.0263

Reference15 articles.

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

2. Artificial intelligence (AI) in urology-Current use and future directions: An iTRUE study

3. 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

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

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