Personalized Mobile Patient Guidance System for Early Detection and Management of Metabolic Syndrome

Abstract

AI-based health recommendation systems can help reduce the risk of delayed or ineffective treatment due to metabolic syndromes by providing tailored advice based on a person's medical history, lifestyle, and other health-related data. AI systems can be used to provide individualized advice, diet plans, customized food, and physical activity advice, daily reminders, risk prediction algorithms, motivational messages, specialized guidance for fitness Persons, AI-powered analyzers, medication schedules, drug development, and create more precise risk forecasts. The most important detail is that the project aims to make a mobile app for metabolic syndrome health assistance popular among people living in remote areas of Sri Lanka. To do this project, the team must collect patient information, analyze patient data, develop personalized recommendations, monitor, and adjust recommendations, and track and update patient data.

Country : Sri Lanka

1 Sanjeevi Chandrasiri2 Suriyaa Kumari3 Udayantha Yapa Y.M.S4 Dissanayaka D.M.R.A5 Herath H.M.T.P6 Peiris B.M.G

  1. Department of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy Road, Malabe, Sri Lanka
  2. Department of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy Road, Malabe, Sri Lanka
  3. Department of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy Road, Malabe, Sri Lanka
  4. Department of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy Road, Malabe, Sri Lanka
  5. Department of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy Road, Malabe, Sri Lanka
  6. Department of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy Road, Malabe, Sri Lanka

IRJIET, Volume 7, Issue 9, September 2023 pp. 118-125

doi.org/10.47001/IRJIET/2023.709013

References

  1. S. J. J. ALIAN, "A PERSONALIZED RECOMMENDATION SYSTEM TO SUPPORT DIABETES SELF-MANAGEMENT FOR AMERICAN INDIANS," IEEE ACCESS, VOL. 6, PP. 73041-73051, 2018. AVAILABLE: HTTPS://IEEEXPLORE.IEEE.ORG/ABSTRACT/DOCUMENT/8539994.
  2. P. Peter T. Katzmarzyk, M. P. Timothy S. Church, P. Ian Janssen, P. Robert Ross and P. Steven N. Blair, "Metabolic Syndrome, Obesity, and Mortality: Impact of cardiorespiratory fitness," Metabolic Syndrome, Obesity, and, vol. 28, 1 February 2005. Available: Metabolic Syndrome, Obesity, and Mortality | Diabetes Care | American Diabetes Association (diabetesjournals.org).
  3. I.T. a. Y. J.-S. Esther Carramolino-Cuéllar, "Relationship between the oral cavity and cardiovascular diseases and metabolic syndrome," 2013 Oct 13. Available: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4048119/.
  4. Y. S. 1. Y. U. 1. A. H. 1. K. I. H. Tanaka 1, "Metabolic syndrome and chronic kidney disease in Okinawa, Japan," vol. 69, pp. 369-374, 2 January 2006.Availablehttps://www.sciencedirect.com/science/article/pii/S0085253815514683.
  5. Zivkovic, Angela M J,   ” Comparative review of diets for the metabolic syndrome: implications for nonalcoholic fatty liver disease"  Available: https://academic.oup.com/ajcn/article/86/2/285/4632978.
  6. F. Alqahtani, "Co-Designing a Mobile App to Improve Mental Health and Well-Being: Focus Group Study," vol. 5, 26.2.2021.Available: JMIR Formative Research - Co-Designing a Mobile App to Improve Mental Health and Well-Being: Focus Group Study.
  7. A.M. Lokesh Khurana, "Obesity and the Metabolic Syndrome in Developing Countries," Clinical Endocrinology & Metabolism, vol. 93, p. s9–s30, 1 November 2008.Available: Obesity and the Metabolic Syndrome in Developing Countries | The Journal of Clinical Endocrinology & Metabolism | Oxford Academic (oup.com).
  8. S. V. 1, "Dynamic Physical Activity Recommendation Delivered through a Mobile Fitness App: A Deep Learning Approach," 18 July 2022. Available: Axioms | Free Full-Text | Dynamic Physical Activity Recommendation Delivered through a Mobile Fitness App: A Deep Learning Approach (mdpi.com).
  9. G. Sannino, "A Wellness Mobile Application for Smart Health: Pilot Study Design and Results," 17 March 2017.Available: Sensors | Free Full-Text | A Wellness Mobile Application for Smart Health: Pilot Study Design and Results (mdpi.com).
  10. M. M. Islam, "Development of an Artificial Intelligence–Based Automated Recommendation System for Clinical Laboratory Tests: Retrospective Analysis of the National Health Insurance Database," vol. 8, 18.11.2020. Available: https://medinform.jmir.org/2020/11/e24163.