Heart Disease and Chronic Kidney Disease Prediction based on Internet of Things using FRNN Algorithm

Even if people are rushing to go to work and have a hectic schedule, they are taking good care of themselves till symptoms appear. Obesity and weight increment are two attributes that affect working on the personal satisfaction across the world. The Internet of Things (IoT), which interconnects, distinguishes, recognizes, and processes information between gadgets or administrations, assumes a basic part in accomplishing the common objective. The Internet of Things (IoT) in healthcare gives us the ability to track, analyses, diagnose, and manage various overweight and obesity diseases. Also, provide weight-loss and obesity prevention solutions. Because there are a limited number of items that may be employed in IoT, another technology, such as machine learning, is being presented to achieve the above-mentioned benefits. People who are at high risk for cardiovascular illness may also be at risk for renal disease, which can be diagnosed and treated using medical information from the past. However, CKD (Chronic Kidney Disease) is a condition that has no analytic signs and is challenging to find, distinguish, and forestall, and it can forever hurt the wellbeing framework, along these lines AI is being utilized to track down it monastery for therapy forecast and examination. The principal objective of this examination is to foster a prescient model for CKD and coronary illness information utilizing open source Python modules. Machine learning algorithms can be used for prediction, and exactness is determined by comparing various algorithms including such K-Nearest Neighbors (KNN) as well as Fast-Recurrent Neural Networks (FRNN). This method is used to forecast a dataset derived from a patient's medical history. The expected number lets us know whether an individual will foster persistent kidney illness or simply not in view of the amount of potassium in their blood.