Proper handling of continuous variables is crucial in healthcare research, for example, within regression modelling for descriptive, explanatory, or predictive purposes. However, inadequate methods ...

The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single ...

BACKGROUND: Primary aldosteronism (PA), an overt form of renin-independent aldosterone production, leads to a disproportionately high rate of major adverse cardiovascular events (MACEs). Mounting ...

This paper is a novel approach to improving the accuracy of wind power generation predictions by using linear regression (LR) algorithm differentiated with the Lasso regression (LaR). The wind power ...

python machine-learning algorithm reinforcement-learning ai genetic-algorithm linear-regression machine-learning-algorithms q-learning evolutionary-algorithms search-algorithm ant-colony-optimization ...

Researchers at EPFL have created a mathematical model that helps explain how breaking language into sequences makes modern AI-like chatbots so good at understanding and using words. The work is ...

For our PAI course project, we are building several disease prediction systems, including heart disease, diabetes, Parkinson's, and breast cancer classification. Using machine learning algorithms, we ...

Population aging is a significant trend in human societal development, emphasizing the urgent need to build a pension service system that aligns with this aging process. Therefore, predicting the ...