Stroke Prediction Based on Support Vector Machine
Hanqing Zhang
Abstract
Stroke needs to be solved as soon as possible because it has made so many people die or become disabled around the world. Therefore, the prediction of stroke is of great importance. In this paper, in order to verify the feasibility of stroke prediction by machine learning, SVM is proposed to predict the stroke. We construct the SVM model to map features about patients’ relevant information to stroke. We use the real dataset to predict the stroke and compare its result with the results of some other models. As a result, we find that SVM can predict the stroke effectively and its result is superior to other’s. Hence, stroke prediction based on SVM can be applied in real life.
Topics & Concepts
Support vector machineStroke (engine)Construct (python library)Computer scienceMachine learningArtificial intelligenceEngineeringMechanical engineeringProgramming languageAcute Ischemic Stroke ManagementArtificial Intelligence in HealthcareRetinal Imaging and Analysis