Results 11 to 20 of about 1,664,785 (304)
Frontiers in Endocrinology, 2023 Background and objectiveThe early identification of modifiable risk factors is important for preventing kidney stones but determining causal associations can be difficult with epidemiological data.
Minghui Liu +20 more
doaj +2 more sources
Healthcare, 2023 In the past two decades, major breakthroughs that improve our understanding of the pathophysiology and therapy of kidney stones (KS) have been lacking. The disease continues to be challenging for patients, physicians, and healthcare systems alike. In this context, epidemiological studies are striving to elucidate the worldwide changes in the patterns ...
Kyriaki Stamatelou, David S. Goldfarb
openaire +3 more sources
Risk of chronic kidney disease in patients with kidney stones—a nationwide cohort study
BMC Nephrology, 2020 Background Chronic kidney disease (CKD) and kidney stones are common in Taiwan; in particular, CKD has a high prevalence but low self-awareness rate.
Tzung-Fang Chuang +5 more
doaj +2 more sources
On the In Vivo Recognition of Kidney Stones Using Machine Learning [PDF]
IEEE Access, 2022 Determining the type of kidney stones allows urologists to prescribe a treatment to avoid the recurrence of renal lithiasis. An automated in-vivo image-based classification method would be an important step towards an immediate identification of the ...
F. López-Tiro +6 more
semanticscholar +1 more source
Gut microbiota in patients with kidney stones: a systematic review and meta-analysis
BMC Microbiology, 2023 Background Mounting evidence indicates that the gut microbiome (GMB) plays an essential role in kidney stone (KS) formation. In this study, we conducted a systematic review and meta-analysis to compare the composition of gut microbiota in kidney stone ...
Tianhui Yuan +10 more
semanticscholar +1 more source
The microbiome of kidney stones and urine of patients with nephrolithiasis
Urolithiasis, 2023 The incidence of nephrolithiasis is rising worldwide. Although it is a multifactorial disease, lifestyle plays a major role in its etiology. Another considerable factor could be an aberrant microbiome.
U. Lemberger +8 more
semanticscholar +1 more source
Deep learning model-assisted detection of kidney stones on computed tomography
International Brazilian Journal of Urology, 2022 Introduction: The aim of this study was to investigate the success of a deep learning model in detecting kidney stones in different planes according to stone size on unenhanced computed tomography (CT) images.
A. Çağlayan +4 more
semanticscholar +1 more source
Assessing deep learning methods for the identification of kidney stones in endoscopic images [PDF]
Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2021 Knowing the type (i.e., the biochemical composition) of kidney stones is crucial to prevent relapses with an appropriate treatment. During ureteroscopies, kidney stones are fragmented, extracted from the urinary tract, and their composition is determined
F. López-Tiro +10 more
semanticscholar +1 more source
Diagnostics, 2022 Recent breakthroughs of deep learning algorithms in medical imaging, automated detection, and segmentation techniques for renal (kidney) in abdominal computed tomography (CT) images have been limited.
Dan Li +10 more
semanticscholar +1 more source
BMJ Open, 2023 Objectives Most kidney stones contain calcium, which is closely associated with human bone health. Therefore, we aimed to determine the relationship between the history of kidney stones and human bone health.
Lei Li +8 more
doaj +1 more source