Machine Learning-Assisted Preoperative Diagnosis of Infection Stones in Urolithiasis Patients-Reference-Cited by-同舟云学术

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

Published:2022-08-01 Issue:8 Volume:36 Page:1091-1098
ISSN:0892-7790
Container-title:Journal of Endourology
language:en
Short-container-title:Journal of Endourology

Author:

Chen TingTing¹²,Zhang YiFan³,Dou QuanLiang³,Zheng XiaoHan¹²,Wang FuSang¹²,Zou JianJun²⁴,Jia RuiPeng³

Affiliation:

1. Department of Clinical Pharmacy, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China.

2. Department of Clinical Pharmacology and Nanjing First Hospital, Nanjing Medical University, Nanjing, China.

3. Department of Urology Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.

4. Department of Pharmacy, Nanjing First Hospital, China Pharmaceutical University, Nanjing, China.

Publisher

Mary Ann Liebert Inc

Subject

Urology

Link

https://www.liebertpub.com/doi/pdf/10.1089/end.2021.0783

Reference34 articles.

1. Renal struvite stones—pathogenesis, microbiology, and management strategies

2. The Case for a More Aggressive Approach to Staghorn Stones

3. Risk factors for sepsis in patients with struvite stones following percutaneous nephrolithotomy

4. Pre- and Postoperative Predictors of Infection-Related Complications in Patients Undergoing Percutaneous Nephrolithotomy

5. Absolute Hounsfield Unit Measurement on Noncontrast Computed Tomography Cannot Accurately Predict Struvite Stone Composition

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Application of AI in urolithiasis risk of infection: a scoping review;Minerva Urology and Nephrology;2024-06

2. A machine learning approach using stone volume to predict stone-free status at ureteroscopy;World Journal of Urology;2024-05-22

3. A nomogram clinical prediction model for predicting urinary infection stones: development and validation in a retrospective study;World Journal of Urology;2024-04-04

4. 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.;Journal of Endourology;2023-10-26

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