Exploring mobile health in a private online social network

Abstract

Health information is very vulnerable. Certain individuals or corporate organisations will continue to steal it similar to bank account data once data is on wireless channels. Once health information is part of a social network, corresponding privacy issues also surface. Insufficiently trained employees at hospitals that pay less attention to creating a privacy-aware culture will suffer loss when mobile devices containing health information are lost, stolen or sniffed. In this work, a social network system is explored as a m-health system from a privacy perspective. A model is developed within a framework of data-driven privacy and implemented on Android operating system. In order to check feasibility of the proposed model, a prototype application is developed on Facebook for different services, including: i) sharing user location; ii) showing nearby friends; iii) calculating and sharing distance moved, and calories burned; iv) calculating, tracking and sharing user heart rate; etc.

Cluster Analysis of Patients’ Clinical Information for Medical Practitioners and Insurance Companies

“…Several types of products have applications for in-patient pharmacy departments. Real-time information technology (IT) systems include (1) automated prescribed order-entry systems, (2) clinical decisionsupport system platforms including intelligent systems to guide treatment and check orders, (4) automated patient records integrated with data from other patient related departments [2][3]. From a business point-of-view, clinical data security is important to maintain edge over competing institutions, since organizations invest huge money to research and development units to develop new drugs, medical devices and medical treatment procedure [4].…”

Machine Learning Based Improved Heart Disease Detection with Confidence

“…Another direction is to facilitate the hospital cardiac team through online social network, similar to the works in [31][32] where patient data can be transported to the hospital system for real time monitoring. This study may also be improved by using a larger heart disease repository to improve training results which may lead to better detection results.…”