mHealth: An Artificial Intelligence Oriented Mobile Application for Personal Healthcare Support
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Published
Jun 9, 2020
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Abstract
Main objective of this study is to introduce an expert system-based mHealth application that takes Artificial Intelligence support by considering previously introduced solutions from the literature and employing possible requirements for a better solution. Thanks to that research study, a mobile software system having Artificial Intelligence support and providing dynamic support against the common health problems in daily life was designed-developed and it was evaluated via survey and diagnosis-based evaluation tasks. Evaluation tasks indicated positive outcomes for the mHealth system.
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How to Cite
AFRAH, Ismail Ali; KOSE, Utku.
mHealth: An Artificial Intelligence Oriented Mobile Application for Personal Healthcare Support.
Journal of Multidisciplinary Developments, [S.l.], v. 5, n. 1, p. 14-30, june 2020.
ISSN 2564-6095.
Available at: <http://www.jomude.com/index.php/jomude/article/view/86>. Date accessed: 21 jan. 2025.
Section
Natural Sciences - Regular Research Paper
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[4] World Health Organization. (2011). mHealth: new horizons for health through mobile technologies. mHealth: new horizons for health through mobile technologies.
[5] Becker, S., Miron-Shatz, T., Schumacher, N., Krocza, J., Diamantidis, C., & Albrecht, U. V. (2014). mHealth 2.0: experiences, possibilities, and perspectives. JMIR mHealth and uHealth, 2(2), e24.
[6] Berrouiguet, S., Barrigón, M. L., Castroman, J. L., Courtet, P., Artés-Rodríguez, A., & Baca-García, E. (2019). Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol. BMC psychiatry, 19(1), 1-9.
[7] Kazantsev, A., Ponomareva, J., & Kazantsev, P. (2014). Development and validation of an AI-enabled mHealth technology for in-home pregnancy management. In 2014 International Conference on Information Science, Electronics and Electrical Eng. (Vol. 2, pp. 927-931). IEEE.
[8] Sannino, G., De Falco, I., & De Pietro, G. (2014). A General-Purpose mHealth System Relying on Knowledge Acquisition through Artificial Intelligence. In Ambient Intelligence-Software and Applications (pp. 107-115). Springer, Cham.
[9] Hemanth, J. D., Kose, U., Deperlioglu, O., & de Albuquerque, V. H. C. (2020). An augmented reality-supported mobile application for diagnosis of heart diseases. The Journal of Supercomputing, 76(2), 1242-1267.
[10] Park, S. H., & Han, K. (2018). Methodologic guide for evaluating clinical performance and effect of artificial intelligence technology for medical diagnosis and prediction. Radiology, 286(3), 800-809.
[11] Divya, S., Indumathi, V., Ishwarya, S., Priyasankari, M., & Devi, S. K. (2018). A self-diagnosis medical chatbot using artificial intelligence. Journal of Web Development and Web Designing, 3(1), 1-7.
[12] Gilavand, A. (2018). Investigating the effect of using mobile educational application of study habits on improving students' awareness concerning proper study habits. J Res Med Dent Sci, 6(5), 273-7.
[13] Yalcin, N., Altun, Y., & Kose, U. (2015). Educational material development model for teaching computer network and system management. Computer Applications in Engineering Education, 23(4), 621-629.
[14] Kose, U., Koc, D., & Yucesoy, S. A. (2013). Design and Development of a Sample" Computer Programming" Course Tool via Story-Based E-Learning Approach. Educational Sciences: Theory and Practice, 13(2), 1235-1250.
[15] Pavaloiu, A., & Kose, U. (2017). Ethical Artificial Intelligence-An Open Question. Journal of Multidisciplinary Developments, 2(2), 15-27.
[16] Cevizoğlu, H. (2019). Artificial Intleligence, Philosophy of Technology and Societal Life (in Turkish), in Artificial Intelligence and Future, Istanbul: Doğu Press.
[17] Giarratano, J. C., & Riley, G. (1998). Expert systems. PWS publishing co..
[18] Yegnanarayana, B. (2009). Artificial neural networks. PHI Learning Pvt. Ltd..
[19] Battiti, R., Brunato, M., & Mascia, F. (2008). Reactive search and intelligent optimization (Vol. 45). Springer Science & Business Media.
[20] Ingle, V., Kogon, S., & Manolakis, D. (2005). Statisical and Adaptive Signal Processing. Artech.
[21] Parker, J. R. (2010). Algorithms for image processing and computer vision. John Wiley & Sons.
[22] Han, J., Pei, J., & Kamber, M. (2011). Data mining: concepts and techniques. Elsevier.
[23] Balkan, F. (2017). Symptoms of Hormonal Diseases (in Turkish). Online (Accessed 03.02.2020):https://www.endokrinoloji.blog/2017/06/25-belirti-ve-neden-oldugu-hastalklar.html