IEEE journal of biomedical and health informatics
Jun 30, 2023
Early diagnosis and prediction of chronic kidney disease (CKD) progress within a given duration are critical to ensure personalized treatment, which could improve patients' quality of life and prolong survival time. In this study, we explore the inte...
Chronic kidney disease (CKD) affects over 850 million people globally, and the need to prevent its development and progression is urgent. During the past decade, new perspectives have arisen related to the quality and precision of care for CKD, owing...
OBJECTIVES: In this systematic review we aimed at assessing how artificial intelligence (AI), including machine learning (ML) techniques have been deployed to predict, diagnose, and treat chronic kidney disease (CKD). We systematically reviewed the a...
To evaluate the differences in baseline chronic kidney disease (CKD) status in correlations between warm ischemic time (WIT) and acute kidney injury (AKI) or acute/chronic renal function change after robot-assisted partial nephrectomy (RAPN). This ...
An accurate estimation of glomerular filtration rate (GFR) is clinically crucial for kidney disease diagnosis and predicting the prognosis of chronic kidney disease (CKD). Machine learning methodologies such as deep neural networks provide a potentia...
Current opinion in nephrology and hypertension
Aug 10, 2022
PURPOSE OF REVIEW: Risk stratification for chronic kidney is becoming increasingly important as a clinical tool for both treatment and prevention measures. The goal of this review is to identify how machine learning tools contribute and facilitate ri...
International journal of urology : official journal of the Japanese Urological Association
Aug 8, 2022
OBJECTIVES: To compare surgical and functional outcomes between robot-assisted laparoscopic partial nephrectomy and open partial nephrectomy in patients with renal cell carcinoma with stage 4 chronic kidney disease.
BMC medical informatics and decision making
Aug 1, 2022
BACKGROUND: Kidney disease progression rates vary among patients. Rapid and accurate prediction of kidney disease outcomes is crucial for disease management. In recent years, various prediction models using Machine Learning (ML) algorithms have been ...
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