Abstract:
Stroke is a significant health concern, with early detection being challenging. Our research employs symptom-based feature selection using chi-square analysis and RFECV. By applying a logistic regression algorithm, we achieved 93% accuracy with just 9 features.
Description:
Supervised by
Mr. Ahmad Shafiullah,
Department of Electrical and Electronic Engineering (EEE)
Islamic University of Technology (IUT)
Board Bazar, Gazipur, Bangladesh
This thesis is submitted in partial fulfillment of the requirement for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2024
