HEALTH PREDICTION SYSTEM POWERED BY MACHINE LEARNING AND IBM CLOUD PAAS

Abstract

Create a system that can change and grow with the healthcare system to solve current problems. Superior treatment for critically ill patients will improve the quality of hospital care. Make regular use of PaaS and machine learning technology to keep an eye on important employees. Enhancingthe healthcare industry's ability to be vigilant and make decisions is the primary objective. The IBM Cloud component is locally built in order to meet financial issues. Among the ensemble learning components used in this model are Naïve Bayes, Logistic Regression, and Decision Tree Classification. The plan's goal is to create a complex system that can foresee important health problems. Rapid remote patient condition evaluation is made possible by the "Critical Patient Management System" (CPMS) software. The program gives doctors access to healthcare management tools that allow them to remotely monitor patients who arein severe condition.