The optimal algorithm, referred to as the OPTIVAN algorithm, was selected and validated using an external cohort (n=268). We evaluated the performance of 4 ML models: gradient boosting machine, random ...

Space vector modulation (SVM) is a sophisticated digital control technique that improves three-phase inverter performance over traditional sinusoidal PWM (SPWM). SVM’s higher DC bus utilization ...

Childhood asthma poses a significant threat to pediatric health, and traditional assessment methods are often inadequate in efficiency and accuracy. This study aims to develop a rapid assessment tool ...

Abstract: To solve the problem of low prediction accuracy of SVM algorithm, this paper proposes a prediction model research method based on PSO-SVM kernel function hybrid algorithm, designs global and ...

🫀 A machine learning project using logistic regression to predict heart disease risk from clinical data. Built with Python, scikit-learn, and Jupyter notebooks. Achieves 85%+ accuracy on 303-patient ...

This repository contains two powerful Python scripts for spam classification using Naïve Bayes and Support Vector Machine (SVM) algorithms. Each script implements a complete pipeline for loading, ...

Arid and semiarid regions face challenges such as bushland encroachment and agricultural expansion, especially in Tiaty, Baringo, Kenya. These issues create mixed opportunities for pastoral and ...

Although an intracranial aneurysm (IA) is widespread and fatal, few drugs can be used to prevent its rupture. This study explored the molecular mechanism and potential targets of IA rupture through ...

Support Vector Machines (SVMs) are a powerful and versatile supervised machine learning algorithm primarily used for classification and regression tasks. They excel in high-dimensional spaces and are ...