Telemedicine Technologies: Big Data, Deep Learning, Robotics, Mobile and Remote Applications for Global Healthcare

Telemedicine Technologies: Big Data, Deep Learning, Robotics, Mobile and Remote Applications for Global Healthcare illustrates the innovative concepts, methodologies and frameworks that will increase the feasibility of the existing telemedicine system. The book also focuses on showcasing prototypes of remote healthcare systems, thus emphasizing the data processing side that is often recognized as the backbone of any telemedicine system.

1. Mobile application for medical diagnosis 2. Emerging Paradigms in Transform-based medical image compression for Telemedicine 3. Adopting m-health in clinical practice – a boon or a bane? 4. Investigation of telecardiology system to detect cardiac abnormalities 5. Microaneurysms detection of early diagnosis of diabetic retinopathy using shape and steerable Gaussian features 6. Telemetry system for early detection of hyperbilirubinemia in neonates 7. WBAN: Driving E-healthcare beyond telemedicine to remote health monitoring-architecture and protocols 8. Remote monitoring of children with chronic illness using wearable vest 9. A predictive model for hypertension diagnosis using machine learning techniques 10. From telediagnosis to teletreatment: The role of computational biology and bioinformatics in tele-based healthcare 11. m-health in public health practice: a constellation of current evidence 12. The Egyptian-African telemedicine network: The treat and teach comprehensive model 13. An extended views based big data model towards facilitating electronic health record analytics 14. Security and Privacy in remote healthcare :Issues, Solutions and Standards 15. Virtual Clinic: A CDSS assisted telemedicine framework