IoT-Enabled health monitoring system with machine learning for real-time risk assessment

Because cardiovascular diseases cause more deaths in the world compared to other health-related issues, they must always be monitored and studied in real-time to avert complications. This essay provides a monitoring system for health in medicine using predictive cardiovascular risk through machine learning and Internet of Things technology. With a simpletons interface, the system gives precise and accurate information regarding health through a Random Forest classifier that collects data from heart rate monitors and lifestyle status. This method would use surgical robots to solve the long-standing issues of inaccurate prediction and non-scalable diagnostic devices while giving new information regarding the problem and preventing potentially deadly situations.