Application Framework for the Prediction of Common Diseases Using Machine Learning

Abstract

The Prediction Framework is a powerful software architecture created to make it machine discovering methods for estimating the probability of getting common diseases based on health data. Without depending on data from smartwatches, this system intends to offer users specific disease risk evaluations and proactive of better understanding of their health. The framework includes a number of essential components. To access their health data, obtain illness forecasts, and risk assessments, users interact with the application framework via a user interface. For collaborative care and data sharing with healthcare experts, the framework connects with external healthcare systems. Smartwatches apart, the health data is gathered from multiple sources and safely kept in the framework's database. Processing the data and using techniques for analysis, which extract pertinent information and produce illness forecasts? Predictions and risk evaluations are made specifically for each user, offering insightful information for illness management and prevention.