[HTML][HTML] Value of artificial intelligence model based on unenhanced computed tomography of urinary tract for preoperative prediction of calcium oxalate monohydrate …
L Tang, W Li, X Zeng, R Wang, X Yang… - Annals of …, 2021 - ncbi.nlm.nih.gov
Background Urolithiasis is a global disease with a high incidence and recurrence rate, and
stone composition is closely related to the choice of treatment and preventive measures …
stone composition is closely related to the choice of treatment and preventive measures …
A combined model based on CT radiomics and clinical variables to predict uric acid calculi which have a good accuracy
Z Wang, G Yang, X Wang, Y Cao, W Jiao, H Niu - Urolithiasis, 2023 - Springer
The aim of this study was to develop a CT-based radiomics and clinical variable diagnostic
model for the preoperative prediction of uric acid calculi. In this retrospective study, 370 …
model for the preoperative prediction of uric acid calculi. In this retrospective study, 370 …
Pure uric acid stone prediction model using the variant coefficient of stone density measured by thresholding 3D segmentation-based methods: A multicenter study
BI Song, J Lee, W Jung, BS Kim - Computer Methods and Programs in …, 2023 - Elsevier
Urinary stones are common urological diseases with increasing prevalence and incidence
worldwide. Among the various types of stones, uric acid stones can be dissolved by oral …
worldwide. Among the various types of stones, uric acid stones can be dissolved by oral …
Predictive modelling of urinary stone composition using machine learning and clinical data: implications for treatment strategies and pathophysiological insights
JA Chmiel, GA Stuivenberg, J Wong, L Nott… - Journal of …, 2023 - liebertpub.com
Purpose: Preventative strategies and surgical treatment for urolithiasis depend on stone
composition. However, stone composition is often unknown until the stone is passed or …
composition. However, stone composition is often unknown until the stone is passed or …
[HTML][HTML] Prediction of the composition of urinary stones using deep learning
US Kim, HS Kwon, W Yang, W Lee, C Choi… - … and Clinical Urology, 2022 - ncbi.nlm.nih.gov
Purpose This study aimed to predict the composition of urolithiasis using deep learning from
urinary stone images. Materials and Methods We classified 1,332 stones into 31 classes …
urinary stone images. Materials and Methods We classified 1,332 stones into 31 classes …
Development and external validation of a machine learning-based model to classify uric acid stones in patients with kidney stones of Hounsfield units< 800
The correct diagnosis of uric acid (UA) stones has important clinical implications since
patients with a high risk of perioperative morbidity may be spared surgical intervention and …
patients with a high risk of perioperative morbidity may be spared surgical intervention and …
Automated classification of urinary stones based on microcomputed tomography images using convolutional neural network
Purpose The classification of urinary stones is important prior to treatment because the
treatments depend on three types of urinary stones, ie, calcium, uric acid, and mixture …
treatments depend on three types of urinary stones, ie, calcium, uric acid, and mixture …
A retrospective study using machine learning to develop predictive model to identify urinary infection stones in vivo
Y Wu, Q Mo, Y Xie, J Zhang, S Jiang, J Guan, C Qu… - Urolithiasis, 2023 - Springer
Preoperative diagnosis of urinary infection stones is difficult, and accurate detection of stone
composition can only be performed ex vivo. To provide guidance for better perioperative …
composition can only be performed ex vivo. To provide guidance for better perioperative …
Predicting urinary stone composition in single-use flexible ureteroscopic images with a convolutional neural network
KT Oh, DY Jun, JY Choi, DC Jung, JY Lee - Medicina, 2023 - mdpi.com
Background and Objectives: Analysis of urine stone composition is one of the most important
factors in urolithiasis treatment. This study investigated whether a convolutional neural …
factors in urolithiasis treatment. This study investigated whether a convolutional neural …
A multicenter study to develop a non-invasive radiomic model to identify urinary infection stone in vivo using machine-learning
J Zheng, H Yu, J Batur, Z Shi, A Tuerxun… - Kidney international, 2021 - Elsevier
Urolithiasis is a common urological disease, and treatment strategy options vary between
different stone types. However, accurate detection of stone composition can only be …
different stone types. However, accurate detection of stone composition can only be …
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