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DOI Prefix: 10.47001/IRJIET

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

Sanjeevi ChandrasiriDepartment of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy Road, Malabe, Sri LankaSuriyaa KumariDepartment of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy Road, Malabe, Sri LankaUdayantha Yapa Y.M.SDepartment of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy Road, Malabe, Sri LankaDissanayaka D.M.R.ADepartment of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy Road, Malabe, Sri LankaHerath H.M.T.PDepartment of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy Road, Malabe, Sri LankaPeiris B.M.GDepartment of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy Road, Malabe, Sri Lanka

Vol 7 No 9 (2023): Volume 7, Issue 9, September 2023 | Pages: 118-125

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 28-09-2023

doi Logo doi.org/10.47001/IRJIET/2023.709013

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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.

Keywords

monitor, metabolic syndromes, AI-based, analyzers, recommendation


Citation of this Article

Sanjeevi Chandrasiri, Suriyaa Kumari, Udayantha Yapa Y.M.S, Dissanayaka D.M.R.A, Herath H.M.T.P, Peiris B.M.G, “Personalized Mobile Patient Guidance System for Early Detection and Management of Metabolic Syndrome” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 7, Issue 9, pp 118-125, September-2023. Article DOI https://doi.org/10.47001/IRJIET/2023.709013
Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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