This study presents valuable findings for identifying biotypes of depression patients using white matter measures, which are under-utilised and under-appreciated in current biological and ...
Background Severe aortic stenosis (AS) is commonly associated with advanced cardiac damage, including right ventricular dysfunction (RVD), pulmonary hypertension (PH) and tricuspid regurgitation (TR), ...
Abstract: This article presents an adaptive ridge regression (ARR)-based data-driven current prediction model aimed at enhancing robustness in permanent magnet synchronous motor (PMSM) drives.
Strong predictive signals don't automatically translate into investable strategies, especially at institutional scale.
Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
A new risk prediction model shows good predictive value in identifying risk for neurogenic bladder (NB) after spinal cord injury (SCI) and guiding clinical interventions, according to a study ...
This study aimed to survey and evaluate the subjective noise annoyance levels in Nairobi City. Being the capital city of Kenya in East Africa, Nairobi is undergoing rapi ...
Read more about From disease detection to biomass forecasting: AI improves aquaculture risk strategy on Devdiscourse ...
1 Department of Mathematics & Statistical Sciences, Jackson State University, Jackson, MS, USA. 2 Department of Public Health, California State University, Fullerton ...
Abstract: Gaussian process regression (GPR) models are becoming increasingly tightly integrated into robotic systems, particularly in the context of robot model predictive control (MPC) operating in ...
A total of 8,598 children were enrolled and classified into three groups: ADHD (n=3,678), subthreshold ADHD (s-ADHD) (n=1,495), and healthy controls (HC) (n=3,425). Data collection covered 40 ...
Chad Beam provides the ins and outs of the implementation of GIS, advanced communication systems and predictive modeling to ensure that staffing, to whatever extent, is utilized most effectively. A ...