References
- Alessa, T., Abdi, S., Hawley, M.S., de Witte, L., (2018). Mobile Apps to Support the Self-Management of Hypertension: Systematic Review of Effectiveness, Usability, and User Satisfaction. JMIR mHealth and uHealth, 6(7).
- Arakawa, T. (2018). Recent Research and Developing Trends of Wearable Sensors for Detecting Blood Pressure. Sensors, 18(9), 2772-2788.10.3390/s18092772
- Athanasiou, T., Darzi, A., (2011). Evidence Synthesis in Healthcare: A Practical Handbook for Clinicians. Springer London.
- Banning, M. (2008). A review of clinical decision making: models and current research. Journal of clinical nursing, 17(2), 187-195.
- Bettinger, B. (2016). Game theory and mechanism design for cooperative competition dilemmas between healthcare providers, PhD Thesis.
- Bevington, P.R., Robinson, D.K., (2003). Data Reduction and Error Analysis for the Physical Sciences. McGraw-Hill.
- Bryan, K. (2009). Communication in Healthcare. Peter Lang Publishing.
- Caplan, A. (2011). Will evidence ever be sufficient to resolve the challenge of cost containment? Journal of Clinical Oncology, 29, 1946–1948.10.1200/JCO.2011.34.7039
- Cappello, C. (2017). Theory of Decision Based on Structural Health Monitoring. PhD Thesis: University of Trento.
- Chobanian, A.V., Bakris, G.L., Black H.R., et al., (2003). Seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure. hypertension, 42(6), 1206-1252.14656957
- Complex Systems Modelling Group. (2010). Modelling in Healthcare. American Mathematical Society.
- Coulter, A. (1997). Partnerships with patients: the pros and cons of shared clinical decision-making. Journal of health services research & policy, 2(2), 112-121.10.1177/135581969700200209
- Drevenhorn, E. (2018). A Proposed Middle-Range Theory of Nursing in Hypertension Care. International journal of hypertension, 2018, 1-11.
- El-Sappagh, S.H., El-Masri, S., (2014). A distributed clinical decision support system architecture. Journal of King Saud University-Computer and Information Sciences, 26(1), 69-78.
- Gorodetsky, V. & Samoylov, V., (2010). Feature extraction for machine learning: logic-probabilistic approach. Feature Selection in Data Mining, (pp. 55-65).
- Guo, F., He, D., Zhang, W., Walton, R.G., (2012). Trends in prevalence, awareness, management, and control of hypertension among United States adults, 1999 to 2010. Journal of the American College of Cardiology, 60(7), 599-606.
- Guyon, I., Elisseeff, A., (2006). An introduction to feature extraction. In Feature extraction (pp. 1-25). Springer.
- Guyon, I., Gunn, S., Nikravesh M., Zadeh, L.A., (2008). Feature Extraction: Foundations and Applications. Springer Berlin Heidelberg.
- Hajjar, I., Kotchen, T.A., (2003). Trends in prevalence, awareness, treatment, and control of hypertension in the United States, 1988-2000. Jama, 290(2), 199-206.
- Hozo, I., Ioannidis, J. P., Djulbegovic, B., (2015). Modern health care as a game theory problem. European journal of clinical investigation, 45(1), 1-12.
- IRMA, Information Resources Management Association. (2018). Digital Curation: Breakthroughs in Research and Practice: Breakthroughs in Research and Practice. IGI Global.
- Kangand, H., Park, H.A., (2015). Development of Hypertension Management Mobile Application based on Clinical Practice Guidelines. European Federation for Medical Informatics (EFMI), 602-606.
- Kiss, I. Z., Georgiou, N., (2018). Game theory can prevent disease outbreaks. Phys.org.
- Landau, J., Borgonovi, E., (2007). Relationship Competence for Healthcare Management: Peer to Peer. Palgrave Macmillan UK.
- Liang, J., He, X., Jia, Y., Zhuand, W., Lei, J., (2018). Chinese Mobile Health APPs for Hypertension Management: A Systematic Evaluation of Usefulness. Journal of healthcare engineering, 1-14.
- Lin, H., Xu, W., Guan, N., Ji, D., et al., (2015). Noninvasive and continuous blood pressure monitoring using wearable body sensor networks. IEEE Intelligent Systems, 38-48.
- Lynch, J.P, Farrar, C.R., Michaels, J.E., (2016). Structural health monitoring: technological advances to practical implementations [scanning the issue]. Proceedings of IEEE, 104(8), 1508-1512.
- Prajwala, T. R. (2015). A comparative study on decision tree and random forest using R tool. International journal of advanced research in computer and communication engineering, 4(1), 196-199.
- Puttini, R., Mahmood, Z., Erl, T., (2013). Cloud Computing: Concepts, Technology & Architecture. Prentice Hall.
- Quick, D., Choo, K.K.R., (2018). Big Digital Forensic Data: Volume 1: Data Reduction Framework and Selective Imaging. Springer Singapore.
- Radha, M., de Groot, K., Rajani N. et al., (2018). Wrist-worn blood pressure tracking in healthy free-living individuals using neural networks. arXiv preprint arXiv:1805.09121.
- Salminen, A., Tompa, F., (2012). Communicating with XML. US: Springer.
- Spaniel, W. (2011). Game Theory 101: The Complete Textbook. CreateSpace Independent Publishing Platform.
- Spencer, P. (1999). XML Design and Implementation. Wrox Press.
- Standing, M. (2008). Clinical judgement and decision-making in nursing--nine modes of practice in a revised cognitive continuum. Journal of Advanced Nursing, 62(1), 124-134.
- Tarrant C., Stokes T., Colman, A.M., (2004). Models of the medical consultation: opportunities and limitations of a game theory perspective. BMJ Quality \& Safety, 13(6), 461-166.15576709
- Vandersluis, K. (2004). Xml-Based Integration with XAware: Unifying Applications and Data in Today's E-Business World. Maximum Press.
- Velickovski, F., Ceccaroni, L., Roca, J.M., Burgos, F., Gáldiz, J.B., Marina, N., & Lluch-Ariet, M., (2014). Clinical Decision Support Systems (CDSS) for preventive management of COPD patients. Journal of translational medicine, 12(2), 59-68.
- Watfa, M. (2011). E-Healthcare Systems and Wireless Communications: Current and Future Challenges: Current and Future Challenges. IGI Global.