Introduction We aimed to determine the association between paternal labour migration and the growth of the left-behind ...

Background The relationship of social determinants of health (SDOH), environmental exposures and medical history to lung function trajectories is underexplored. A better understanding of these ...

Interpretability of Support Vector Machine (SVM) or Neural Networks (NN) models, examples of black-box models, is a field of study that has recently gained attention, especially for the significant ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

Choosing the right curve fit model is essential for revealing key data features, such as rate of change, asymptotes, and EC 50 /IC 50 values. The best model is the one that most faithfully reflects ...

Artificial intelligence models can secretly transmit dangerous inclinations to one another like a contagion, a recent study found. Experiments showed that an AI model that’s training other models can ...

This project implements a quadratic nonlinear regression model to estimate the real-world distance between a hand and a camera based on the relative positions of hand landmarks in 2D images. The ...

R Symons Electric Vehicles, a U.K.-based electric vehicle dealer, drove two nearly identical Tesla Model 3s 200 miles for a range and efficiency test. Despite one car having 225,000 miles, it was just ...

What is linear regression in machine learning ? Understanding Linear Regression in machine learning is considered as the basis or foundation in machine learning. In this video, we will learn what is ...

Zachary del Rosario receives funding from the National Science Foundation and Toyota Research Institute. Nicknamed “Galloping Gertie” for its tendency to bend and undulate, the Tacoma Narrows Bridge ...

Linear multiplicative models are popular tools for analyzing data with positive responses. However, the linear structure of models is too restrictive on the regression relation, which may lead to a ...