Nephrology

Artificial Intelligence in Efficient Diabetes Care.

Diabetes is a chronic disease that is not easily curable but can be managed efficiently. Artificial Intelligence is a powerful tool that may help in diabetes prediction, continuous glucose monitoring, Insulin injection guidance, and other areas of diabetes care. Diabetes, if not appropriately managed, leads to secondary complications like retinopathy, nephropathy, and neuropathy. Artificial intell...

A novel method for conformity assessment testing of dialysis machines for post-market surveillance purposes.

BACKGROUND: Dialysis machines are used regularly in healthcare practice. They are classified as a type of medical device with moderate and high risk therefore significant requirements are placed on their safety and performance every time they are used on patients. The new Medical Device Regulation (MDR) defines medical device post-market surveillance (PMS) as performed by independent, third-party,...

Review of Artificial Intelligence-Based Signal Processing in Dialysis: Challenges for Machine-Embedded and Complementary Applications.

Artificial intelligence technology is trending in nearly every medical area. It offers the possibility for improving analytics, therapy outcome, and u...

Deep Learning Using Electrocardiograms in Patients on Maintenance Dialysis.

Cardiovascular morbidity and mortality occur with an extraordinarily high incidence in the hemodialysis-dependent end-stage kidney disease population....

A knowledge-based decision support system for inferring supportive treatment recommendations for diabetes mellitus.

BACKGROUND: Diabetes Mellitus (DM) is a significant risk, mostly causing blindness, kidney failure, heart attack, stroke, and lower limb amputation. A...

[COMPARING LAPAROSCOPIC AND ROBOT-ASSISTED PYELOPLASTY FOR URETERO-PELVIC JUNCTION OBSTRUCTION: INITIAL EXPERIENCE FROM A SINGLE CENTER].

(Objective) To compare the initial results of robot-assisted laparoscopic pyeloplasty (RALP) and laparoscopic pyeloplasty (LP) for uretero-pelvic junc...

Continuous Renal Replacement Therapy: What Have We Learned And What Are Key Milestones For The Years To Come?

Continuous renal replacement therapy (CRRT) is the main extracorporeal kidney support therapy used in critical ill patients in the intensive care unit...

Machine learning for the prediction of acute kidney injury in critical care patients with acute cerebrovascular disease.

PURPOSE: Acute kidney injury (AKI) is a common complication and associated with a poor clinical outcome. In this study, we developed and validated a m...

Artificial intelligence in peritoneal dialysis: general overview.

OBJECTIVE: This article is a general overview about artificial intelligence/machine learning (AI/ML) algorithms in the domain of peritoneal dialysis (...

Estimation of Mycophenolic Acid Exposure in Chinese Renal Transplant Patients by a Joint Deep Learning Model.

BACKGROUND: To predict mycophenolic acid (MPA) exposure in renal transplant recipients using a deep learning model based on a convolutional neural net...

Development and deployment of interpretable machine-learning model for predicting in-hospital mortality in elderly patients with acute kidney disease.

BACKGROUND: Acute kidney injury (AKI) is more likely to develop in the elderly admitted to the intensive care unit (ICU). Acute kidney disease (AKD) a...

Comment on: "Are nephrometry scores accurate for the prediction of outcomes in patients with renal angiomyolipoma treated with robot-assisted partial nephrectomy? A multi-institutional analysis." The point of view by J-ERUS/YAU Working Group on Robot-Assisted Surgery.

[Clinical analysis of three-dimensional surgical planning system for guiding robot-assisted selective artery clamping partial nephrectomy in completely endophytic renal tumor].

To examine the safety and feasibility of three-dimensional (3D) surgical planning system for guiding robot-assisted selective artery clamping partial...

Prediction of pathological staging and grading of renal clear cell carcinoma based on deep learning algorithms.

OBJECTIVE: Deep learning algorithms were used to develop a model for predicting the staging and grading of renal clear cell carcinoma to inform clinic...

Application of neural network approach for modelling COD reduction from real refinery effluent by electrocoagulation.

The present study aims to investigate the feasibility of implementing the electrocoagulation (EC) process to treat Algiers refinery effluent. The elec...

A framework of deep learning networks provides expert-level accuracy for the detection and prognostication of pulmonary arterial hypertension.

AIMS: To test the hypothesis that deep learning (DL) networks reliably detect pulmonary arterial hypertension (PAH) and provide prognostic information...

End-to-end interstitial fibrosis assessment of kidney biopsies with a machine learning-based model.

BACKGROUND: The extent of interstitial fibrosis in the kidney not only correlates with renal function at the time of biopsy but also predicts future r...

Redo Robotic Partial Nephrectomy for Recurrent Renal Tumors: A Multi-Institutional Analysis.

As the experience with robot-assisted partial nephrectomy (RAPN) grows, the indications have expanded to incorporate previously operated ipsilateral ...

Feasibility of Deep Learning-Based Analysis of Auscultation for Screening Significant Stenosis of Native Arteriovenous Fistula for Hemodialysis Requiring Angioplasty.

OBJECTIVE: To investigate the feasibility of using a deep learning-based analysis of auscultation data to predict significant stenosis of arteriovenou...

Abdomen tissues segmentation from computed tomography images using deep learning and level set methods.

Accurate abdomen tissues segmentation is one of the crucial tasks in radiation therapy planning of related diseases. However, abdomen tissues segmenta...