Nephrology

Latest AI and machine learning research in nephrology for healthcare professionals.

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Dietary patterns associated with the incidence of hypertension among adult Japanese males: application of machine learning to a cohort study.

PURPOSE: The previous studies that examined the effectiveness of unsupervised machine learning metho...

Machine learning application identifies plasma markers for proteinuria in metastatic colorectal cancer patients treated with Bevacizumab.

BACKGROUND AND OBJECTIVES: Proteinuria is a common complication after the application of bevacizumab...

Artificial intelligence support in MR imaging of incidental renal masses: an early health technology assessment.

OBJECTIVE: This study analyzes the potential cost-effectiveness of integrating an artificial intelli...

Integrated machine learning and deep learning for predicting diabetic nephropathy model construction, validation, and interpretability.

OBJECTIVE: To construct a risk prediction model for assisted diagnosis of Diabetic Nephropathy (DN) ...

[Artificial intelligence and acute kidney injury].

Digitalization is increasingly finding its way into intensive care units and with it artificial inte...

Risk factors of recurrence after robot-assisted laparoscopic partial nephrectomy for solitary localized renal cell carcinoma.

To evaluate the recurrence rate and risk factors of recurrence after robot-assisted laparoscopic par...

Elevated Plasma CXCL8 Concentrations in Significant Fibrosis but Not in Subclinical Rejection After Adult Liver Transplantation.

BACKGROUND: The noninvasive detection of subclinical graft injury including subclinical T cell-media...

Epidemiology of Epstein-Barr Virus Chronic High Viral Load in Kidney Transplant Recipients.

BACKGROUND: Epstein-Barr virus (EBV) chronic high viral load (CHVL) may be defined by >16 000 copies...

The importance of data in Pulmonary Arterial Hypertension: from international registries to Machine Learning.

Real-world registries have been critical to building the scientific knowledge of rare diseases, incl...

A fully automatic deep learning-based method for segmenting regions of interest and predicting renal function in pediatric dynamic renal scintigraphy.

OBJECTIVE: Accurate delineation of renal regions of interest (ROIs) is critical for the assessment o...

[Robot-assisted kidney transplantation-what is new?].

BACKGROUND: The first robot-assisted kidney transplantation (RAKT) was conducted in 2010, and the fi...

Initial Experience in Urological Surgery with a Novel Robotic Technology: Magnetic-Assisted Robotic Surgery in Urology.

Magnetic-assisted robotic surgery (MARS) has been developed to maximize patient benefits of minimal...

Deep learning applications for kidney histology analysis.

PURPOSE OF REVIEW: Nephropathology is increasingly incorporating computational methods to enhance re...

Deep-learning-based renal artery stenosis diagnosis via multimodal fusion.

PURPOSE: Diagnosing Renal artery stenosis (RAS) presents challenges. This research aimed to develop ...

Deep learning algorithm (YOLOv7) for automated renal mass detection on contrast-enhanced MRI: a 2D and 2.5D evaluation of results.

INTRODUCTION: Accurate diagnosis and treatment of kidney tumors greatly benefit from automated solut...

Deep Learning for Automated Detection and Localization of Traumatic Abdominal Solid Organ Injuries on CT Scans.

Computed tomography (CT) is the most commonly used diagnostic modality for blunt abdominal trauma (B...

Investigation on explainable machine learning models to predict chronic kidney diseases.

Chronic kidney disease (CKD) is a major worldwide health problem, affecting a large proportion of th...

Enhancing heart failure treatment decisions: interpretable machine learning models for advanced therapy eligibility prediction using EHR data.

Timely and accurate referral of end-stage heart failure patients for advanced therapies, including h...

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