Cardio Monitoring and Cardiac disease Prediction Using Machine Learning

Heart disease is the biggest cause of death in the globe. The method of predicting cardiac diseaseand monitoring is exceedingly complex. It can only be done properly if the doctor has a lot ofexpertise and is well-versed in the condition. IoT-based illness prediction is a relatively recenttechnology for accurately classifying diseases based on sensor data. This system proposes anenhanced deep learning-based framework for predicting the heart disease. The general publiclyavailable Hungarian heart disease dataset is utilized for the implementation, which includes heartdisease related data collected from patients through IoT sensor devices. The body sensor networksis one of the core technologies of IoT developments in health care system. IoT and GSM basedmonitoring system is proposed for continuous monitoring of patient’s health condition usingdifferent sensors. The Internet of Things (IoT) with smartphone technologies contains vastapplications in solving the problems of heart diseases in patients needing care. With wirelesssensors and smart devices, remote monitoring can identify the real-time physical status of heartpatients during normal physical activities. Doctor can monitor the patient condition on his/her smartphone.