Significant predictors were selected on the training set using recursive feature elimination methods, followed by prediction model development using 7 machine learning algorithms (logistic regression, ...

Abstract: Recently, there has been growing attention on combining quantum machine learning (QML) with classical deep learning approaches as computational techniques are key to improving the ...

Background: Alterations in brain structure have been suggested to be associated with bulimia nervosa (BN). This study aimed to employ machine learning (ML) methods based on diffusion tensor imaging ...

Introduction: Artificial intelligence (AI) marks a new wave of the information technology revolution and permeates various sectors as an indispensable tool. Despite its widespread adoption, its ...

Dr. McBain studies policies and technologies that serve vulnerable populations. On any given night, countless teenagers confide in artificial intelligence chatbots — sharing their loneliness, anxiety ...

Apple’s MLX machine learning framework, originally designed for Apple Silicon, is getting a CUDA backend, which is a pretty big deal. Here’s why. The work is being led by developer @zcbenz on GitHub ...

The stroke deprives person's brain of oxygen and nutrients, which can cause brain cells to die. Numerous works have been carried out for predicting various diseases by comparing the performance of ...

Furthermore, the XGB model demonstrated the most accurate calibration across all prediction windows, with values of 0.129, 0.136, 0.144, and 0.148, respectively. Additionally, decision curve analysis ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...