International Journal of Advancements in Technology
Open Access

Department of Artificial Intelligence, Laboratory of Signal, Image processing and Energy Mastery (SIME), Higher National School of Engineers (ENSIT), University of Tunis, Tunisia

Publications

• Research Article   
  Brain Stroke Classification Using Ensemble Learning Approaches
  Author(s): Houmem Slimi* and Sabeur Abid
  
  Brain Stroke (BS) is one of leading cause of death among humans. Early stroke symptoms must be recognized in order to forecast stroke and encourage a healthy lifestyle. In this study, Machine Learning (ML) techniques were used to build and evaluate a number of models with the goal of developing a reliable framework for estimating the longterm risk of having a stroke. This study's main objective is to introduce a stacking method, which has proven to perform exceptionally well as evidenced by a variety of metrics, including AUC, precision, recall, F-measure and accuracy. The experimental results demonstrate the stacking classification method's superiority over competing strategies by achieving a remarkable AUC of 98.6%, as well as high F-measure, precision and recall rates of 98.4% each and a 98.5% total accuracy... View More»
  

  Abstract PDF