The XGBoost model exhibited optimal performance in the training ... ROC curve analysis of five machine learning algorithms in the training dataset for predicting the long-term prognosis of HICH ...

To address this challenge, researchers developed SAVANA, a new algorithm which they describe in the journal Nature Methods. SAVANA uses machine learning to accurately identify structural variants ...

Machine learning models, including XGBoost, Random Forest, Support Vector Machine, and k-Nearest Neighbors, were trained for ED risk prediction. Key predictors included advanced age, smoking history, ...

A weekly newsletter that helps demystify artificial intelligence. Founded at the Massachusetts Institute of Technology in 1899, MIT Technology Review is a world-renowned, independent media company ...

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This project applies various machine learning models—especially XGBoost—to classify ECG heartbeat signals from the MIT-BIH Arrhythmia Database. Advanced metaheuristic optimization algorithms are used ...

In this paper, we propose an effective electrocardiogram (ECG) signal classification method using XGBoost classifier. The ECG signals are passed through four phases of data acquisition, noise ...

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