The pre-transplant weight loss required of end-stage renal disease patients is often unachievable. Though robot-assisted procedures among extremely obese have shown minimal complication, long-term outcomes are understudied. Previously, we reported no...
Identifying progressive early chronic kidney disease (CKD) patients at a health checkup is a good opportunity to improve their prognosis. However, it is difficult to identify them using common health tests. This worksite-based cohort study for 7 year...
This paper introduces a deep-learning based computer-aided diagnostic (CAD) system for the early detection of acute renal transplant rejection. For noninvasive detection of kidney rejection at an early stage, the proposed CAD system is based on the f...
BACKGROUND: The diagnosis of gastric cancer mainly relies on endoscopy, which is invasive and costly. The aim of this study is to develop a predictive model for the diagnosis of gastric cancer based on noninvasive characteristics.
Severely burned and non-burned trauma patients are at risk for acute kidney injury (AKI). The study objective was to assess the theoretical performance of artificial intelligence (AI)/machine learning (ML) algorithms to augment AKI recognition using ...
OBJECTIVE: To develop a radial basis function (RBF) neural network and investigate its performance in the estimation of glomerular filtration rate (GFR) for patients with chronic kidney disease.
This work aims to explore risk factors for ischemic stroke in young adults and analyze the Traditional Vascular Risk Factors Model based on age, hypertension, diabetes, smoking history, and drinking history. Further, the Lipid Metabolism Model was an...
BACKGROUND: Accurate estimating glomerular filtration rate (GFR) is crucial both in clinical practice and epidemiological survey. We incorporated semi-supervised learning technology to improve GFR estimation performance.
BACKGROUND: Despite the kidney supply shortage, 18%-20% of deceased donor kidneys are discarded annually in the United States. In 2018, 3569 kidneys were discarded.