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Title: Intelligent, secured smart app for complete diabetes lifestyle management –“Diabeta”
Authors: Jayasekara, J. T. N. N.
Gunasekera, R. H.
Ravindu Hasanka, V. G.
Hasintha Kashmika, H. B. G.
Suriyaa Kumari, P. K.
Ravi Supunya Swarnakanthac, N. H. P.
Keywords: Non-Invasive
Diabetes Prediction
Machine Learning
Issue Date: 15-Nov-2022
Publisher: Faculty of Applied Sciences, South Eastern University of Sri Lanka, Sammanthurai.
Citation: 11th Annual Science Research Sessions 2022 (ASRS-2022) Proceedings on "“Scientific Engagement for Sustainable Futuristic Innovations”. 15th November 2022. Faculty of Applied Sciences, South Eastern University of Sri Lanka, Sammanthurai, Sri Lanka. pp. 21.
Abstract: Especially today's society tends to use new technological devices instead of relying on on document materials in daily life. While there are diabetes-related apps that more accurately predict users' prediabetes or diabetes type 2 using machine learning approaches, predicting health risks by analyzing glucose monitoring data, recommend meal and exercise plans, and use a non-invasive approach to measure and monitor blood glucose level, heart rate, and blood oxygen level, and over Wi-Fi using NodeMCU makes the proposed DiaBeta application unique among diabetes applications. Other secondary functions such as digital logbook, reminders, lifestyle-based meal recommendations, medical guidelines, and efforts such as glucose monitoring data can be easily performed with a smartphone. DiaBeta is a life-saving app that can be used by anyone around the world to get a more accurate and personalized meal plan. DiaBeta offers a precise, clinical, validated, and standardized solution for diabetes patients.
ISBN: 978-624-5736-60-7
Appears in Collections:11th Annual Science Research Session - FAS

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