Brain Stroke Prediction Using Random Forest Algorithm

Author(s)	M.N.V.S.S. Abhiram, T. Sudheer, Y. Shanmuk Ram Tej, A.N.V.K. Swarupa
Country	India
Abstract	The research focuses on early brain stroke detection using AI-based methods. A VGG16 CNN model extracts features from CT scans, which are then classified using a Random Forest algorithm. The approach achieves high accuracy, outperforming other techniques, enabling quicker and more accurate stroke detection for early medical intervention.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 16, Issue 1, January-March 2025
Published On	2025-03-31
Cite This	Brain Stroke Prediction Using Random Forest Algorithm - M.N.V.S.S. Abhiram, T. Sudheer, Y. Shanmuk Ram Tej, A.N.V.K. Swarupa - IJSAT Volume 16, Issue 1, January-March 2025. DOI 10.71097/IJSAT.v16.i1.3059
DOI	https://doi.org/10.71097/IJSAT.v16.i1.3059
Short DOI	https://doi.org/g9dgpw

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