Predictive Analysis on Multimodal Medicare Application

Predictive analysis nowadays is determining the future events influenced by past actions and behavior that are primarily based on concepts of machine learning, deep learning artificial intelligence, statistics, data analytics and mathematical modeling to give accurate insights of prediction. Tools implied on various sectors including marketing, retail manufacturing and finance. But in the medicare sector predictive analysis has proved to have greater impact on doctors and patients for analyzing health issues, operations and treatments that mitigate potential risks that arise in predicting root causes of diseases in patients. It aimed to provide better services and diagnosis by advanced technology to improve health treatments. Predictive analysis here provides customized and automated tools to look for diseases in the larger data set comprising past patient's test volumes with their diagnosis history for better medical practices. Incorporating existing tools used in the healthcare sector with advanced tools can also help in prevention of future diseases in patients by regular checkups that mitigate potential risk of abnormality in them with benefits including appointments, regular checkups, disease prevention, fraud detection and save time, money and resources. This paper will focus on the importance of predictive analytics in healthcare and different predictive models that can be used in solving problems of such fatal diseases.