The integration of expert systems, mobile intelligence, and the cloud for diabetes diagnosis was the study's
main objective. An expert system is a computer programme that makes use of a knowledge base and an inference engine
to resolve problems considerably more quickly and effectively than they would otherwise. To lessen the limitations of
mobile applications, the cloud has provided developers with a variety of services to create, manage, and deploy. Because
of population expansion, ageing, addiction, urbanization, obesity, lack of exercise, and other complex diseases, there are
more people with diabetes than ever before. Furthermore, these issues are made worse by a lack of specialists, inaccurate
diagnoses, and inadequate medical facilities. Thus, diabetics require ongoing care such as dietary restriction, exercise,
and insulin management. A hospital's knowledge was drawn from in order to create the prototype using a purposive
sampling technique. Case studies are chosen for testing and assessing the prototype system in order to determine whether
or not it is accurate and meets end-user criteria.
Keywords
Artificial Intelligence, Expert System, Diabetes, Cloud Computing, Google platform, Firebase.
R. Salari, S. R Niakan Kalhori, M. GhaziSaeedi, M. Jeddi, M. Nazari, and F. Fatehi, “Mobile-Based and Cloud-Based System for Self-management of People With Type 2 Diabetes: Development and Usability Evaluation,” Journal of Medical Internet Research, vol. 23, no. 6, p. e18167, Jun. 2021, doi: 10.2196/18167.
O. A., O. N., and J. O., “Online Support System for Diabetes Management,” International Journal of Computer Applications, vol. 152, no. 10,pp. 6–11, Oct. 2016, doi: 10.5120/ijca2016911454.
M.Ahmed, M. Alfonse, A. M.Mahmoud, And A.-B. M.Salem, “Knowledge Acquisition for Developing Knowledge-Base of Diabetic Expert System,” The 7th International Conference on Information Technology, May 2015, doi: 10.15849/icit.2015.0004.
M. Akter and M. Shorif Uddin, “Android-based Diabetes Management System,” International Journal of Computer Applications, vol. 110, no.10, pp. 5–9, Jan. 2015, doi: 10.5120/19350-0071.
Al-ghamdi, A. A., Wazzan, M. A., Mujallid, F. M., & Bakhsh, N. K. (2011). An Expert System of Determining Diabetes Treatment Based on Cloud Computing Platforms, 2(5), 1982– 1987.
J. L. ALTY, “Expert System Building Tools,” Topics in Expert System Design - Methodologies and Tools, pp. 181–204, 1989, doi:10.1016/b978-0-444-87321-7.50012-0.
V. Bhandari and R. Kumar, “Comparative Analysis of Fuzzy Expert Systems for Diabetic Diagnosis,” International Journal of Computer Applications, vol. 132, no. 6, pp. 8–14, Dec. 2015, doi: 10.5120/ijca2015907424.
Jian-xun Chen, Shih-Li Su, and Che-Ha Chang, “Diabetes care decision support system,” 2010 2nd International Conference on Industrial and Information Systems, Jul. 2010, doi: 10.1109/indusis.2010.5565846.
B. R. Gaines and M. L. G. Shaw, “Eliciting knowledge and transferring it effectively to a knowledge-based system,” IEEE Transactions on Knowledge and Data Engineering, vol. 5, no. 1, pp. 4–14, 1993, doi: 10.1109/69.204087.
Gebremariam, S. (2013). Self-Learning Knowledge Based System For School Of Graduate Studies, (January). Gebrye
H. M. (2016). Integrating Expert System For Vegetable Disease Diagnosis And Treatment In Tigray Region , Ethiopia : Focus On Tomato And Onio, (November).
George, J. (2014). Cloud Based Diabetes Management and Research - Blue Circled Cloud,3(1), 1–6. Guidance for Industry and Food. (2016).
Ibrahim M.Ahmed, Abeer M.Mahmoud, Mostafa Aref, A.-B. M. S. (2017). A study on Expert Systems for Diabetic Diagnosis and Treatment. 65 International Diabetes Federation. (2018). What is Diabetes.
R. A. Kowalski, “The early years of logic programming,” Communications of the ACM, vol. 31, no. 1, pp. 38–43, Jan. 1988, doi:10.1145/35043.35046.
Kumar, P. S. J., & Chaithra, M. A. S. (2015). A Survey on Cloud Computing based Health Care for Diabetes : Analysis and Diagnosis, 17(4), 109–117. https://doi.org/10.9790/0661- 1741109117
Mehta , Bhavin M Madhani , Nishay Patwardhan, R. (2017). Firebase : A Platform for your Web and Mobile Applications, 2017.
Patra, P. S. K. (2012). Automatic Diagnosis of Diabetes by Expert System, 9(2), 299– 304.
Singh, T. (2001). Prototype Expert System for Diagnosis and Treatment of Diabetes, 2001.
Tan, C. (2008). A Prototype of Knowledge- Based System for Fault Diagnosis in Automatic Wire Bonding Machine, 32, 235–244.
WHO, N. (1999). Definition, diagnosis and classification of diabetes and its complication, 1999.
Cite this article
Praveen Kumar M, Santhoshkumar S P, Chandramohan S, “Identification of Diabetes with Mobile Applications using Cloud Based Expert System”, Advances in Computational Intelligence in Materials Science, pp. 089-101, May. 2023. doi:10.53759/acims/978-9914-9946-9-8_15
