Research directions for kidney stone disease
Kidney stone disease poses a major burden to patients and healthcare systems around the world. The formation of kidney stones may occur over months or years, but many patients are diagnosed at a late stage, suffer excruciating pain, and require surgical intervention to physically remove the stones. The prevalence of kidney stones has increased during recent decades to over 10% in many developed countries, suggesting a link with environmental and behavioral factors. Recurrence rates are also high. In terms of their impact and scale, kidney stones are an ongoing pandemic. The causes and mechanisms of kidney stone formation are diverse and often unknown, resulting in varied compositions and different anatomical locations being affected. A better understanding of these processes could enable earlier diagnoses through more sensitive and scalable biomarkers, as well as more effective preventives and therapeutics.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Lightweight Framework for Automated Kidney Stone Detection using coronal CT images
Kidney stone disease results in millions of annual visits to emergency departments in the United States. Computed tomography (CT) scans serve as the standard imaging modality for efficient detection of kidney stones. Var…
Computed Tomography (CT)CPUHybrid Deep Learning Framework for Classification of Kidney CT Images: Diagnosis of Stones, Cysts, and Tumors
Medical image classification is a vital research area that utilizes advanced computational techniques to improve disease diagnosis and treatment planning. Deep learning models, especially Convolutional Neural Networks (C…
Deep Learningimage-classificationImage ClassificationMedical Image ClassificationUSCNet: Transformer-Based Multimodal Fusion with Segmentation Guidance for Urolithiasis Classification
Kidney stone disease ranks among the most prevalent conditions in urology, and understanding the composition of these stones is essential for creating personalized treatment plans and preventing recurrence. Current metho…
A CNN Approach to Polygenic Risk Prediction of Kidney Stone Formation
Kidney stones are a common and debilitating health issue, and genetic factors play a crucial role in determining susceptibility. While Genome-Wide Association Studies (GWAS) have identified numerous single nucleotide pol…
The Open Kidney Ultrasound Data Set
Ultrasound, because of its low cost, non-ionizing, and non-invasive characteristics, has established itself as a cornerstone radiological examination. Research on ultrasound applications has also expanded, especially wit…
Semantic Segmentation