A Cloud-based App for Early Detection of Type II Diabetes with the Aid of Deep Learning
- Resource Type
- Conference
- Authors
- Miazi, Zubair Azim; Jahan, Shahriar; Niloy, Md. A. K.; Roknuzzaman; Shama, Anika; Rahman, Md. Zianur; Islam, Md. R.; Badal, Faisal R.; Das, Sajal K.
- Source
- 2021 International Conference on Automation, Control and Mechatronics for Industry 4.0 (ACMI) Automation, Control and Mechatronics for Industry 4.0 (ACMI), 2021 International Conference on. :1-6 Jul, 2021
- Subject
- Communication, Networking and Broadcast Technologies
Power, Energy and Industry Applications
Robotics and Control Systems
Deep learning
Machine learning algorithms
Mechatronics
Predictive models
Prediction algorithms
Diabetes
Monitoring
Android Application
Deep Learning
Type II Diabetes Mellitus (T2DM)
Diabetes Type II Predictor (DT2P)
- Language
Diabetes is a medical condition that has affected millions around the world and still doing it at an increasing rate. Many researches show that an early detection of diabetes can prevent risk-factors that can be caused as a result of this disease. The inclusion of machine learning and deep learning algorithms in the early prediction of diabetes has played a big role in the health-care monitoring system. Many of the early researches put emphasis on improving the accuracy of prediction models but often, the datasets available are too short for deep learning algorithms to leverage their true potential. In this research, along with a highly accurate deep learning model, a new system has been proposed integrating cloud services where users can directly contribute to enrich an existing dataset which also can be used in improving accuracy of the deep learning methods. The model proposed in this research shows promising results on predicting diabetes and the proposed system ensures usage from anywhere in the world with contribution in further enriching an existing dataset.