Stroke is the cause of death and disability in the global population. Patients often suffer from strokes because poor living habits. In recent years, artificial intelligence (AI) has become a hot topic in various fields, especially in medical applications. In this article, patient's physiological data is used to build model for predicting stroke in an artificial neural networks (ANNs). The ANNs method proposed in this paper can reach about 98% in classification accuracy under the condition of 1000 times cross-validation.
• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL