A Medical Cyber-Physical System utilizing the Bayes algorithm for post-diagnosis patient supervision
Main Article Content
Abstract
Among several basic human needs, medical treatment is one of the most prominent. However, since there need to be more doctors, nurses, and other medical facilities in many places, medical cyber-physical systems are quickly becoming a competitive alternative. One important use of these systems is for observation after a diagnosis. Instead of active observation by a caregiver, this can be easily done using various monitoring systems. However, most of the existing systems for this application are inflexible and need to consider the current challenges. On the other hand, these problems can be solved by intelligent and adaptive systems, which is now possible thanks to the growth of relevant technology, especially healthcare 4.0. Therefore, this article proposes an adaptive system based on the Bayes algorithm for performing medical interventions on patients, leading to a reduction in the dependence on caregivers, particularly in the post-diagnosis scenario.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
AJSE contents are under the terms of the Creative Commons Attribution License. This permits anyone to copy, distribute, transmit and adapt the worknon-commercially provided the original work and source is appropriately cited.
References
[2] M. Al Karim, M. Y. Ara, M. M. Masnad, M. Rasel, and D. Nandi, “Student performance classification and prediction in fully online envi-ronment using decision tree,” AIUB Journal of Science and Engineering (AJSE), vol. 20, no. 3, pp. 70–76, 2021.
[3] A. Bhowmik, M. S. U. Miah, et al., “Iot (internet of things)-based smart garbage management system,” AIUB Journal of Science and Engineering (AJSE), vol. 19, no. 1, pp. 33–40, 2020.
[4] L. Sha, S. Gopalakrishnan, X. Liu, and Q. Wang, “Cyber-physical systems: A new frontier,” in 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008), 2008, pp. 1–9.
[5] M. S. U. Miah, T. B. Sarwar, S. S. Islam, M. S. Haque, M. Masuduzza-man, and A. Bhowmik, “An adaptive medical cyber-physical system for post diagnosis patient care using cloud computing and machine learning approach,” in 2022 3rd International Conference for Emerging Technology (INCET), 2022, pp. 1–6.
[6] X. Li, L. Wei, W. Shang, X. Xing, M. Yin, J. Ling, K. Mao, Y. Zhu, and K. Yang, “Trace and evaluation systems for health services quality in rural and remote areas: a systematic review,” Journal of Public Health, vol. 26, no. 2, pp. 127–135, 2018.
[7] P. Antsaklis, “Goals and challenges in cyber-physical systems research editorial of the editor in chief,” IEEE Transactions on Automatic Control, vol. 59, no. 12, pp. 3117–3119, 2014.
[8] E. K. Wang, Y. Ye, X. Xu, S. M. Yiu, L. C. K. Hui, and K. P. Chow, “Security issues and challenges for cyber physical system,” in 2010 IEEE/ACM Int’l Conference on Green Computing and Communications & Int’l Conference on Cyber, Physical and Social Computing, 2010, pp.733–738.
[9] F. Zhang, K. Szwaykowska, W. Wolf, and V. Mooney, “Task scheduling for control oriented requirements for cyber-physical systems,” in 2008 Real-Time Systems Symposium, 2008, pp. 47–56.
[10] N. Dey, A. S. Ashour, F. Shi, S. J. Fong, and J. M. R. Tavares, “Medical cyber-physical systems: A survey,” Journal of medical systems, vol. 42, no. 4, pp. 1–13, 2018.
[11] H. Qiu, M. Qiu, M. Liu, and G. Memmi, “Secure health data sharing for medical cyber-physical systems for the healthcare 4.0,” IEEE Journal of Biomedical and Health Informatics, vol. 24, no. 9, pp. 2499–2505, 2020.
[12] A. Mehedi, A. H. Tokee, S. Islam, and M. S. U. Miah, “Iot based healthcare middleware,” in Proceedings of the International Conference on Computing Advancements, 2020, pp. 1–4.
[13] J. Lin, S. Sedigh, and A. Miller, “A general framework for quantitative modeling of dependability in cyber-physical systems: A proposal for doctoral research,” in 2009 33rd Annual IEEE International Computer Software and Applications Conference, vol. 1, 2009, pp. 668–671.
[14] J. I. Jimenez, H. Jahankhani, and S. Kendzierskyj, “Health care in the cyberspace: Medical cyber-physical system and digital twin challenges,” in Digital twin technologies and smart cities. Springer, 2020, pp. 79–92.
[15] K. H ̈ayrinen, K. Saranto, and P. Nyk ̈anen, “Definition, structure, content, use and impacts of electronic health records: a review of the research literature,” International journal of medical informatics, vol. 77, no. 5, pp. 291–304, 2008.
[16] S. A. Haque, S. M. Aziz, and M. Rahman, “Review of cyber-physical system in healthcare,” international journal of distributed sensor net-works, vol. 10, no. 4, p. 217415, 2014.
[17] N. Stevens, A. R. Giannareas, V. Kern, A. Viesca, M. Fortino-Mullen, A. King, and I. Lee, “Smart alarms: multivariate medical alarm inte-gration for post cabg surgery patients,” in Proceedings of the 2nd ACM
SIGHIT International Health Informatics Symposium, 2012, pp. 533–542.
[18] J. Shi, J. Wan, H. Yan, and H. Suo, “A survey of cyber-physical systems,” in 2011 International Conference on Wireless Communications and Signal Processing (WCSP), 2011, pp. 1–6.
[19] I. Lee and O. Sokolsky, “Medical cyber physical systems,” in Design Automation Conference, 2010, pp. 743–748.
[20] H. Chen, “Applications of cyber-physical system: a literature review,” Journal of Industrial Integration and Management, vol. 2, no. 03, p. 1750012, 2017.
[21] NITRD, “ABOUT THE NETWORKING AND INFORMATION TECHNOLOGY RESEARCH AND DEVELOPMENT (NITRD) PROGRAM.” [Online]. Available: https://www.nitrd.gov/about/
[22] S. K. Jha, “Medical cyber physical system,” International Journal of Emerging Technology and Advanced Engineering, vol. 4, no. 5, pp. 819–823, 2014.
[23] S. Gupta, M. Mittal, and A. Padha, “Predictive analytics of sensor data based on supervised machine learning algorithms,” in 2017 International Conference on Next Generation Computing and Information Systems (ICNGCIS), 2017, pp. 171–176.