About this document
Machine Learning for Stroke Diagnosis by abhilashasingh8791 is a document available to read on EtoBox.
1. The document reviews research on using machine learning algorithms like random forests to predict strokes using physiological indicators, with random forests achieving 96% accuracy. 2. It examines attribute selection methods for stroke prediction and defines a stroke as a focal vascular brain injury shown on imaging over 24 hours. 3. It discusses using data mining classification techniques on hospital data to create a 95% accurate stroke prediction model, finding certain medical conditions increase s
- Author
- abhilashasingh8791
- Language
- EN