Design and implementation of a secure patient recommender and prediction system

Abstract

Early disease prediction can help sick persons determine the severity of the disease and take quick action, thus, a healthcare recommended system is viewed as additional tools to help patients control and manage their ill-health. Medical recommended system which provides users with quick and optimal disease predictions has been in existence for a while; however, it is faced with several data security issues. Sometimes, patients confidential data which are stored of the archive after each recommendation may be accessed by unauthorized persons, and this can warrant a serve data breach and disclosure of private medical information. Thus, the focus of our project is to design a privacy-aware recommended system that not just makes facilitates quick and easy recommendation for sick persons but also securely protects stored medical information from unauthorized access. This system will be designed to support quick search, recommendation septimal confidentiality and integrit