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Stroke Risk Prediction Using SVM by Lê Chí Danh is a document available to read on EtoBox.

What is Stroke Risk Prediction Using SVM about?

The document discusses the use of Support Vector Machine (SVM) for predicting stroke risk, highlighting its effectiveness in classifying patients based on various health indicators. The model achieved an accuracy of 0.77 and a recall of 0.83, indicating its potential to assist in patient classification in emergency settings. Despite its success, the study acknowledges the need for further improvements to align with modern medical technologies.

Author

Lê Chí Danh

Language

EN