A cloud-based framework for Home-diagnosis service over big medical data

Abstract

Self-caring services are becoming more and more important for our daily life, especially under the urgent situation of global aging. Big data such as massive historical medical records makes it possible for users to have self-caring services, such as to get diagnosis by themselves with similar patients’ records. Developing such a self-caring service gives rises to challenges including highly concurrent and scalable medical record retrieval, data analysis, as well as privacy protection. In this paper, we propose a cloud-based framework for implementing a self-caring service named Home-diagnosis to address the above challenges. Concretely, a Lucene-based distributed search cluster is designed to support highly concurrent and scalable medical record retrieval, data analysis and privacy protection. Moreover, to speed up medical record retrieval, a Hadoop cluster is adopted for offline data storage and index building. The implementation of the Home-diagnosis service is discussed, where similar historical medical records as well as a disease-symptom lattice are obtained, to help users figure out which kind of disease they are probably infected with. Finally, a prototype system is designed and a running example is presented to demonstrate the scalability and efficiency of our proposal.