Diabetes Predicting mHealth Application Using Machine Learning

With the advancement of information technologies, mobile health (mHealth) technologies can be leveraged for patient self-management, patient diagnosis and determining the probability of being affected by some disease. Diabetes mellitus is a chronic and lifestyle disease and millions of people from a...

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Bibliographic Details
Published in2017 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON ECE) pp. 237 - 240
Main Authors Khan, Nabila Shahnaz, Muaz, Mehedi Hasan, Kabir, Anusha, Islam, Muhammad Nazrul
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2017
Subjects
Conferences
Diabetes
Diseases
Machine learning
mobile health
naive Bayes classifier
Prediction algorithms
prediction application
Sugar
survey
Online AccessGet full text
DOI10.1109/WIECON-ECE.2017.8468885

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Summary:With the advancement of information technologies, mobile health (mHealth) technologies can be leveraged for patient self-management, patient diagnosis and determining the probability of being affected by some disease. Diabetes mellitus is a chronic and lifestyle disease and millions of people from all over the world fall victim to it. Although there are some mobile apps keeping track of calories, sugar taken, medicine doses, lifestyle, blood glucose, blood pressure, weight of individuals and giving suggestion about food, exercises to prevent or control diabetes, no application has been found that was explicitly developed to analyze the risk of being a diabetic patient. Therefore, the objective of this paper is to develop an intelligent mHealth application based on machine learning to assess his/her possibility of being diabetic, prediabetic or nondiabetic without the assistance of any doctor or medical tests.
DOI:10.1109/WIECON-ECE.2017.8468885