AIMC Topic: Kidney Diseases

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Robot-assisted laparoscopic unroofing and fulguration of sequestered caliceal diverticula cluster.

Journal of pediatric urology
INTRODUCTION: We report a rare case of four sequestered caliceal diverticula that failed previous percutaneous sclerotherapy and were subsequently managed with robot-assisted laparoscopic unroofing and fulguration of the sequestered diverticula clust...

Identification of glomerular lesions and intrinsic glomerular cell types in kidney diseases via deep learning.

The Journal of pathology
Identification of glomerular lesions and structures is a key point for pathological diagnosis, treatment instructions, and prognosis evaluation in kidney diseases. These time-consuming tasks require a more accurate and reproducible quantitative analy...

Inspection of visible components in urine based on deep learning.

Medical physics
PURPOSE: Urinary particles are particularly important parameters in clinical urinalysis, especially for the diagnosis of nephropathy. Therefore, it is highly important to precisely detect urinary particles in the clinical setting. However, artificial...

Role of Artificial Intelligence in Kidney Disease.

International journal of medical sciences
Artificial intelligence (AI), as an advanced science technology, has been widely used in medical fields to promote medical development, mainly applied to early detections, disease diagnoses, and management. Owing to the huge number of patients, kidne...

Classification of glomerular hypercellularity using convolutional features and support vector machine.

Artificial intelligence in medicine
Glomeruli are histological structures of the kidney cortex formed by interwoven blood capillaries, and are responsible for blood filtration. Glomerular lesions impair kidney filtration capability, leading to protein loss and metabolic waste retention...

Automatic kidney segmentation in ultrasound images using subsequent boundary distance regression and pixelwise classification networks.

Medical image analysis
It remains challenging to automatically segment kidneys in clinical ultrasound (US) images due to the kidneys' varied shapes and image intensity distributions, although semi-automatic methods have achieved promising performance. In this study, we pro...

Radiologic-Radiomic Machine Learning Models for Differentiation of Benign and Malignant Solid Renal Masses: Comparison With Expert-Level Radiologists.

AJR. American journal of roentgenology
The objective of our study was to compare the performance of radiologicradiomic machine learning (ML) models and expert-level radiologists for differentiation of benign and malignant solid renal masses using contrast-enhanced CT examinations. This ...

A hybrid neural network model for predicting kidney disease in hypertension patients based on electronic health records.

BMC medical informatics and decision making
BACKGROUND: Disease prediction based on Electronic Health Records (EHR) has become one hot research topic in biomedical community. Existing work mainly focuses on the prediction of one target disease, and little work is proposed for multiple associat...

Renal Function Impairment in Kidney Transplantation: Importance of Early BK Virus Detection.

Transplantation proceedings
BACKGROUND: BK virus allograft nephropathy is a major complication of kidney transplantation that markedly reduces graft survival (50% graft failure 24 months after being diagnosed). BK virus replication can occur at any time posttransplantation. Vir...