AI Medical Compendium Topic

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Kidney

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Identification of glomerulosclerosis using IBM Watson and shallow neural networks.

Journal of nephrology
BACKGROUND: Advanced stages of different renal diseases feature glomerular sclerosis at a histological level which is observed by light microscopy on tissue samples obtained by performing a kidney biopsy. Computer-aided diagnosis (CAD) systems levera...

Using Machine Learning to Identify Metabolomic Signatures of Pediatric Chronic Kidney Disease Etiology.

Journal of the American Society of Nephrology : JASN
BACKGROUND: Untargeted plasma metabolomic profiling combined with machine learning (ML) may lead to discovery of metabolic profiles that inform our understanding of pediatric CKD causes. We sought to identify metabolomic signatures in pediatric CKD b...

Introducing robot-assisted laparoscopic donor nephrectomy after experience in retroperitoneal endoscopic approach: a matched propensity score analysis.

ANZ journal of surgery
OBJECTIVES: To assess the safety and efficacy of introducing robotic-assisted laparoscopic donor nephrectomy (RALDN) to the standard retroperitoneal endoscopic donor nephrectomy (REDN).

MBANet: Multi-branch aware network for kidney ultrasound images segmentation.

Computers in biology and medicine
Due to the influence of kidney morphology, heterogeneous structure and image quality, segmenting kidney in ultrasound images is challenging. To alleviate this challenge, we proposed a novel deep neural network architecture, namely Multi-branch Aware ...

Automatic Evaluation of Histological Prognostic Factors Using Two Consecutive Convolutional Neural Networks on Kidney Samples.

Clinical journal of the American Society of Nephrology : CJASN
BACKGROUND AND OBJECTIVES: The prognosis of patients undergoing kidney tumor resection or kidney donation is linked to many histologic criteria. These criteria notably include glomerular density, glomerular volume, vascular luminal stenosis, and seve...

A deep-learning toolkit for visualization and interpretation of segmented medical images.

Cell reports methods
Generalizability of deep-learning (DL) model performance is not well understood and uses anecdotal assumptions for increasing training data to improve segmentation of medical images. We report statistical methods for visual interpretation of DL model...

High-Throughput, Label-Free and Slide-Free Histological Imaging by Computational Microscopy and Unsupervised Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Rapid and high-resolution histological imaging with minimal tissue preparation has long been a challenging and yet captivating medical pursuit. Here, the authors propose a promising and transformative histological imaging method, termed computational...

A neural network for glomerulus classification based on histological images of kidney biopsy.

BMC medical informatics and decision making
BACKGROUND: Computer-aided diagnosis (CAD) systems based on medical images could support physicians in the decision-making process. During the last decades, researchers have proposed CAD systems in several medical domains achieving promising results....