Support vector machines improve classification by mapping inseparable signals into higher-dimensional spaces. Random forest models, through ensemble decision trees, increase robustness against ...

Abstract: Social media has become a crucial communication medium during disasters, producing large volumes of user-generated content that, if properly filtered, can provide responders with timely and ...

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...

This retrospective study developed ML prognostic models for 3-month functional outcome (modified Rankin scale scores of 3–6) in IVT-treated AIS patients. A derivation cohort (n = 938) was split 7:3 ...

Stroke remains one of the leading causes of global mortality and long-term disability, driving the urgent need for accurate and early risk prediction tools. Traditional models such as the Framingham ...

Abstract: —The objective is to more accurately forecast phishing attacks that harvest sensitive data from unsuspecting users by utilizing Logistic Regression in comparison to the Novel Random Forest ...

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Random forest machine learning regression and interactive web application using home loan data to help determine algorithmic discrimination toward race and gender in ...