Open Heart

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure

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 ...

Machine Learning for C++ developers: DMLLib and VisualDML

Here’s a quick library to write your GPU-based operators and execute them in your Nvidia, AMD, Intel or whatever, along with my new VisualDML tool to design your operators visually. This is a follow ...
Devdiscourse

Rising heat, resilient markets: What AI reveals about livestock economics

Heat stress is widely recognized as a critical risk factor in livestock systems. Rising temperatures and humidity levels can ...
The Lancet

Incidence and costs of cervical spondylosis in urban China from 2013 to 2017: a nationwide population-based study

As the population ages, China will face an ever-increasing burden from CS. Strategies targeting elder population and high-risk groups should be prioritized in the establishment of management related ...
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
IEEE

Design of a Wideband dB-Linear Variable Gain Amplifier With Continuous Gain Adjusting in 90-nm CMOS Technology

Abstract: This paper presents a wideband dB-linear variable-gain amplifier (VGA) with a DC-offset cancellation network in a 90-nm CMOS technology for high-speed applications. The VGA consists of a ...
IEEE

A Belief Rule Base Considering Random Variables of Adaptive Membership Functions

Abstract: With its inherent causal reasoning and superior capacity for handling uncertainty, the belief rule base (BRB) has been widely applied in complex systems modeling. As a generalization of ...
SciELO

Investigation of eighth-grade students' understanding of the slope of the linear function

This study aimed to investigate eighth-grade students' difficulties and misconceptions and their performance of translation between the different representation modes related to the slope of linear ...
SciELO

Multiple linear regression and random forest to predict and map soil properties using data from portable X-ray fluorescence spectrometer (pXRF)

Soil analyses; spatial prediction; proximal sensor. On the other hand, carrying out laboratory tests in a large number of samples requires more time and financial resources, as well as chemical ...
Frontiers

Accuracy of attribute estimation in the crossed random effects linear logistic test model: impact of Q-matrix misspecification

A simulation study is designed to explore the accuracy of attribute parameter estimation in the crossed random effects linear logistic test model (CRELLTM) with the impact of Q-matrix misspecification ...
GitHub

RandONets - MATLAB Code (J. Comp. Phys). RandONets (Random projection-based Operator Networks) is a MATLAB implementation designed for learning efficiently linear and nonlinear ...

We present a machine learning method based on random projections with Johnson-Lindenstrauss (JL) and/or Rahimi and Recht (2007) Random Fourier Features (RFFN) for efficiently learning linear and ...