Development Of Electronic Data Analytics For Public Health Surveillance And Epidemiology

Abstract

The process of assessing patient data that is taken from various medical devices is known as health care analytics. The patient's condition is projected by the analytics, which helps the physician support the diagnosis. The data created are referred to as Electronic Health Records (EHR) / Electronic Medical Records (EMR). Large volumes of electronic health and medical records being produced, giving rise to the idea of medical big data. Medical data may be in its early stages of development or fully developed and organised. The data research community now has a new way to experiment with medical data and access the results of intelligent algorithms through testing or historical experiences. The vast amount of medical big data used in this study project served as the impetus for an attempt to handle the data using supervised classifiers and predictors from clever machine learning techniques.  In healthcare, this analytical model is used to forecast illnesses. The goal of this project is to develop an intelligent framework for mining large amounts of medical data in order to assess public health issues and forecast illness occurrences.