Nephrology

Acute kidney injury and its impact on renal prognosis after robot-assisted laparoscopic radical prostatectomy.

BACKGROUND: This study assessed the incidence and impact of acute kidney injury (AKI) on renal progn...

Artificial intelligence for anterior segment diseases: Emerging applications in ophthalmology.

With the advancement of computational power, refinement of learning algorithms and architectures, an...

Using human in vitro transcriptome analysis to build trustworthy machine learning models for prediction of animal drug toxicity.

During the development of new drugs or compounds there is a requirement for preclinical trials, comm...

Using Artificial Intelligence Resources in Dialysis and Kidney Transplant Patients: A Literature Review.

BACKGROUND: The purpose of this review is to depict current research and impact of artificial intell...

An improved clear cell renal cell carcinoma stage prediction model based on gene sets.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcino...

Using machine learning models to predict the initiation of renal replacement therapy among chronic kidney disease patients.

Starting renal replacement therapy (RRT) for patients with chronic kidney disease (CKD) at an optima...

Estimating Blood Pressure from the Photoplethysmogram Signal and Demographic Features Using Machine Learning Techniques.

Hypertension is a potentially unsafe health ailment, which can be indicated directly from the blood ...

Application of explainable ensemble artificial intelligence model to categorization of hemodialysis-patient and treatment using nationwide-real-world data in Japan.

BACKGROUND: Although dialysis patients are at a high risk of death, it is difficult for medical prac...

Technological Innovation in Outpatient Assistance for Chronic Liver Disease and Liver Transplant Patients During the Coronavirus Disease Outbreak: A Method to Minimize Transmission.

Optimization of dialysate bicarbonate in patients treated with online haemodiafiltration.

BACKGROUND: Metabolic acidosis is a common problem in haemodialysis patients, but acidosis overcorre...

Lower Incidence of Postoperative Acute Kidney Injury in Robot-Assisted Partial Nephrectomy Than in Open Partial Nephrectomy: A Propensity Score-Matched Study.

Acute kidney injury (AKI) after partial nephrectomy is attributed to parenchymal reduction and isch...

Results of Green Indocyanine in the Use of the R1T1 Robot as Aid in the Pre-operative Process of Hepatic Organ Transplant: Experiment in Wistar Rats.

Since the beginning of the history of transplants, numerous difficulties have been faced in the effe...

Agalsidase beta treatment slows estimated glomerular filtration rate loss in classic Fabry disease patients: results from an individual patient data meta-analysis.

BACKGROUND: Fabry disease is a rare, X-linked genetic disorder that, if untreated in patients with t...

Predictive modeling of blood pressure during hemodialysis: a comparison of linear model, random forest, support vector regression, XGBoost, LASSO regression and ensemble method.

BACKGROUND: Intradialytic hypotension (IDH) is commonly occurred and links to higher mortality among...

Machine-learning based exploration of determinants of gray matter volume in the KORA-MRI study.

To identify the most important factors that impact brain volume, while accounting for potential coll...

Correlation of Measured and Estimated Creatinine Clearance in Hospitalized Elderly Patients: A Retrospective Cohort Study.

Accurate assessment of renal function is essential in hospitalized elderly patients. Few studies ha...

Evolution of renal function in patients with severe intestinal failure on home parenteral nutrition.

BACKGROUND: Kidney disease is a frequent but underestimated complication in patients suffering from ...

Prediction of hypertension, hyperglycemia and dyslipidemia from retinal fundus photographs via deep learning: A cross-sectional study of chronic diseases in central China.

Retinal fundus photography provides a non-invasive approach for identifying early microcirculatory a...

Using Machine Learning to Predict Early Onset Acute Organ Failure in Critically Ill Intensive Care Unit Patients With Sickle Cell Disease: Retrospective Study.

BACKGROUND: Sickle cell disease (SCD) is a genetic disorder of the red blood cells, resulting in mul...

A deep learning algorithm to detect chronic kidney disease from retinal photographs in community-based populations.

BACKGROUND: Screening for chronic kidney disease is a challenge in community and primary care settin...

Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in Korea.

Herein, we aim to assess mortality risk prediction in peritoneal dialysis patients using machine-lea...