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Kidney stones are mineral deposits in the renal calyces and pelvis that are found free or attached to the renal papillae. They contain crystalline and organic components and are formed when the urine becomes supersaturated with respect to a mineral. Calcium oxalate is the main constituent of most stones, many of which form on a foundation of calcium ...
Khan, Saeed R+7 more
+14 more sources
PurposeAlthough food insecurity is a major public health concern associated with various diseases, the relationship between food insecurity and kidney stones remains unclear.
Wei Wang, Xi Lu, Yixiao Shi, Xin Wei
doaj +1 more source
The microbiome of kidney stones and urine of patients with nephrolithiasis
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
Assessing deep learning methods for the identification of kidney stones in endoscopic images [PDF]
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
Kidney stone disease (KSD) and recurrent urinary tract infections (rUTI) are frequently concomitant conditions. We conducted a systematic review to determine the association of UTI in patients with KSD and to assess the outcomes of kidney stone treatment
F. Ripa+5 more
semanticscholar +1 more source
Objective Several studies have suggested a potential link between use of proton pump inhibitors (PPIs) and the risk of kidney stones, attributed to alterations in urine mineral levels.
Ming Liu+4 more
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Deep learning model-assisted detection of kidney stones on computed tomography
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
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
Lateralization of uric acid stones on the left side
The analysis of 35,087 kidney stones revealed that 60% of uric acid stones originate from the left kidney whereas other stones are homogeneously distributed ...
Letavernier, Emmanuel+8 more
doaj +1 more source