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Constriction, Pathologic

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Machine Learning Classification for Assessing the Degree of Stenosis and Blood Flow Volume at Arteriovenous Fistulas of Hemodialysis Patients Using a New Photoplethysmography Sensor Device.

Sensors (Basel, Switzerland)
The classifier of support vector machine (SVM) learning for assessing the quality of arteriovenous fistulae (AVFs) in hemodialysis (HD) patients using a new photoplethysmography (PPG) sensor device is presented in this work. In clinical practice, the...

Levenberg-Marquardt Neural Network Algorithm for Degree of Arteriovenous Fistula Stenosis Classification Using a Dual Optical Photoplethysmography Sensor.

Sensors (Basel, Switzerland)
This paper proposes a noninvasive dual optical photoplethysmography (PPG) sensor to classify the degree of arteriovenous fistula (AVF) stenosis in hemodialysis (HD) patients. Dual PPG measurement node (DPMN) becomes the primary tool in this work for ...

A novel method of artery stenosis diagnosis using transfer function and support vector machine based on transmission line model: A numerical simulation and validation study.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Transfer function (TF) is an important parameter for the analysis and understanding of hemodynamics when arterial stenosis exists in human arterial tree. Aimed to validate the feasibility of using TF to diagnose arterial ste...

Robotic-Assisted Ureteral Re-implantation: A Case Series.

Journal of laparoendoscopic & advanced surgical techniques. Part A
INTRODUCTION: Minimally invasive surgical techniques are currently used for numerous urologic disorders and generally offer decreased morbidity and equivalent outcomes compared with open surgery. There is a relative paucity of data on robot-assisted ...

Improving accuracy of vascular access quality classification in hemodialysis patients using deep learning with K highest score feature selection.

The Journal of international medical research
OBJECTIVE: To develop and evaluate a novel feature selection technique, using photoplethysmography (PPG) sensors, for enhancing the performance of deep learning models in classifying vascular access quality in hemodialysis patients.