[HTML][HTML] Machine learning versus conventional clinical methods in guiding management of heart failure patients—a systematic review
Abstract Machine learning (ML) algorithms “learn” information directly from data, and their
performance improves proportionally with the number of high-quality samples. The aim of …
performance improves proportionally with the number of high-quality samples. The aim of …
A brief review of hypernetworks in deep learning
Hypernetworks, or hypernets in short, are neural networks that generate weights for another
neural network, known as the target network. They have emerged as a powerful deep …
neural network, known as the target network. They have emerged as a powerful deep …
[HTML][HTML] Comparing the performance of published risk scores in Brugada syndrome: a multi-center cohort study
Abstract The management of Brugada Syndrome (BrS) patients at intermediate risk of
arrhythmic events remains controversial. The present study evaluated the predictive …
arrhythmic events remains controversial. The present study evaluated the predictive …
Design of microchannel heat sink with wavy channel and its time-efficient optimization with combined RSM and FVM methods
In this study, a sinusoidal wavy structure of microchannel heat sink intended for active
cooling of compact electronic devices such as insulated-gate bipolar transistor (IGBT) has …
cooling of compact electronic devices such as insulated-gate bipolar transistor (IGBT) has …
Multi-depot vehicle routing problem for hazardous materials transportation: A fuzzy bilevel programming
Due to enormous demand and potential threat to public, hazardous materials transportation
has been tremendously investigated in recent years. However, there are few studies …
has been tremendously investigated in recent years. However, there are few studies …
Predictions of diabetes complications and mortality using hba1c variability: a 10-year observational cohort study
Introduction Emerging evidence suggests that HbA1c variability, in addition to HbA1c itself,
can be used as a predictor for mortality. The present study aims to examine the predictive …
can be used as a predictor for mortality. The present study aims to examine the predictive …
[HTML][HTML] Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning
Introduction Recent studies have reported that HbA1c and lipid variability is useful for risk
stratification in diabetes mellitus. The present study evaluated the predictive value of the …
stratification in diabetes mellitus. The present study evaluated the predictive value of the …
[HTML][HTML] Sodium-glucose cotransporter 2 (SGLT2) inhibitors vs. dipeptidyl peptidase-4 (DPP4) inhibitors for new-onset dementia: a propensity score-matched …
Introduction: The effects of sodium-glucose cotransporter 2 inhibitors (SGLT2I) and
dipeptidyl peptidase-4 inhibitors (DPP4I) on new-onset cognitive dysfunction in type 2 …
dipeptidyl peptidase-4 inhibitors (DPP4I) on new-onset cognitive dysfunction in type 2 …
Natural convection heat transfer in a nanofluid-filled cavity with double sinusoidal wavy walls of various phase deviations
In the present study, a new 2D quarter-circular enclosure with two sinusoidal wavy walls and
two straight walls was proposed. Natural convection heat transfer in such cavities filled with …
two straight walls was proposed. Natural convection heat transfer in such cavities filled with …
[HTML][HTML] Development of a multivariable prediction model for severe COVID-19 disease: a population-based study from Hong Kong
Recent studies have reported numerous predictors for adverse outcomes in COVID-19
disease. However, there have been few simple clinical risk scores available for prompt risk …
disease. However, there have been few simple clinical risk scores available for prompt risk …