An intelligent epileptic seizure disease prediction model using enhanced feature extraction with classification techniques

Abstract

Big data applications have introduced the large-scale distribution applications that work with large data sets. Data analysis problem plays a vital role in many sectors. The existing software s for big data applications generates a large amount of intermediate data. There are many applications of big data such as manufacturing, bioinformatics, health care, social network, business, science and technology and smart cities. In the healthcare industry, various sources for big data comprises of hospital records, medical records of patients, results of medical assessments, and so on. The big data analytics of health care is still a challenging and time-demanding task. Health care sectors can achieve their development and accurately perform medical data analysis and early disease detection with the use of big medical data. newlineThe main objective is to provide the effective and automatic detection of epileptic seizure classification using intelligent feature extraction with machine learning models. Epilepsy is an emerging disease distinguished by constant likelihood for growing epileptic seizures. A seizure is a brief occurrence of symptoms or signs in the brain caused by abnormally high or synchronised neuronal activity. A seizure does not necessarily mean that a person has epilepsy, unless the criteria for diagnosis of epilepsy are met. If not properly treated in the early stage also results in severe health issues and even some times to mortality. newline