![](/images/graphics-bg.png)
Design and Development of Diabetes Management System Using Machine Learning
Joint Authors
Sowah, Robert A.
Bampoe-Addo, Adelaide A.
Armoo, Stephen K.
Saalia, Firibu K.
Gatsi, Francis
Sarkodie-Mensah, Baffour
Source
International Journal of Telemedicine and Applications
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-16
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
This paper describes the design and implementation of a software system to improve the management of diabetes using a machine learning approach and to demonstrate and evaluate its effectiveness in controlling diabetes.
The proposed approach for this management system handles the various factors that affect the health of people with diabetes by combining multiple artificial intelligence algorithms.
The proposed framework factors the diabetes management problem into subgoals: building a Tensorflow neural network model for food classification; thus, it allows users to upload an image to determine if a meal is recommended for consumption; implementing K-Nearest Neighbour (KNN) algorithm to recommend meals; using cognitive sciences to build a diabetes question and answer chatbot; tracking user activity, user geolocation, and generating pdfs of logged blood sugar readings.
The food recognition model was evaluated with cross-entropy metrics that support validation using Neural networks with a backpropagation algorithm.
The model learned features of the images fed from local Ghanaian dishes with specific nutritional value and essence in managing diabetics and provided accurate image classification with given labels and corresponding accuracy.
The model achieved specified goals by predicting with high accuracy, labels of new images.
The food recognition and classification model achieved over 95% accuracy levels for specific calorie intakes.
The performance of the meal recommender model and question and answer chatbot was tested with a designed cross-platform user-friendly interface using Cordova and Ionic Frameworks for software development for both mobile and web applications.
The system recommended meals to meet the calorific needs of users successfully using KNN (with k=5) and answered questions asked in a human-like way.
The implemented system would solve the problem of managing activity, dieting recommendations, and medication notification of diabetics.
American Psychological Association (APA)
Sowah, Robert A.& Bampoe-Addo, Adelaide A.& Armoo, Stephen K.& Saalia, Firibu K.& Gatsi, Francis& Sarkodie-Mensah, Baffour. 2020. Design and Development of Diabetes Management System Using Machine Learning. International Journal of Telemedicine and Applications،Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1174198
Modern Language Association (MLA)
Sowah, Robert A.…[et al.]. Design and Development of Diabetes Management System Using Machine Learning. International Journal of Telemedicine and Applications No. 2020 (2020), pp.1-17.
https://search.emarefa.net/detail/BIM-1174198
American Medical Association (AMA)
Sowah, Robert A.& Bampoe-Addo, Adelaide A.& Armoo, Stephen K.& Saalia, Firibu K.& Gatsi, Francis& Sarkodie-Mensah, Baffour. Design and Development of Diabetes Management System Using Machine Learning. International Journal of Telemedicine and Applications. 2020. Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1174198
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1174198