BACKGROUND: Random forest (RF) is a machine-learning method that generally works well with high-dimensional problems and allows for nonlinear relationships between predictors; however, the presence of correlated predictors has been shown to impact it...
Klinicheskaia laboratornaia diagnostika
Jan 1, 2018
The purpose of the study was to investigate gender features of abnormalities of blood serum lipid composition and their relationship with clinical and functional manifestations in patients with chronic kidney disease (CKD). The study covered patients...
Combinatorial chemistry & high throughput screening
Jan 1, 2018
AIMS AND OBJECTIVES: Solid Lipid Nanoparticles (SLNs) are pharmaceutical delivery systems that have advantages such as controlled drug release, long-term stability etc. Particle Size (PS) is one of the important criteria of SLNs. These factors affect...
BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases. Machine learning techniques were introduced to evaluate the optimal predictive clinical model of NAFLD.
The effect of chronic metabolic acidosis (MA) on cardiovascular disease (CVD) in the setting of chronic kidney disease (CKD) is largely unknown. Therefore, we aimed to study this relationship in nondialysis CKD patients.This cross-sectional, single-c...
Alimentary pharmacology & therapeutics
Aug 1, 2017
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) affects 20%-40% of the general population in developed countries and is an increasingly important cause of hepatocellular carcinoma. Electronic medical records facilitate large-scale epidemiologic...
BACKGROUND AND AIMS: Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease worldwide. Risk factors for NAFLD disease progression and liver-related outcomes remain incompletely understood due to the lack of computa...
Journal of nutritional science and vitaminology
Jan 1, 2016
This study investigated the effect of a single oral ingestion of alpha-linolenic acid-enriched diacylglycerol (ALA-DAG) on postprandial serum triglyceride (TG) levels. A randomized, double-blind, controlled, crossover study was performed in subjects ...
Statistical models to predict incident diabetes are often based on limited variables. Here we pursued two main goals: 1) investigate the relative performance of a machine learning method such as Random Forests (RF) for detecting incident diabetes in ...