Machine Learning Embedded Smartphone Application for Early-Stage Diabetes Risk Assessment

Author:

Shuvo Md Maruf Hossain1,Ahmed Nafis1,Islam Humayera2,Alaboud Khuder2,Cheng Jianlin1,Mosa Abu Saleh Mohammad2,Islam Syed Kamrul3

Affiliation:

1. Department of Electrical Engineering and Computer Science

2. Institute for Data Science and Informatics and Center for Biomedical Informatics

3. University of Missouri,Columbia,MO,USA,65211

Publisher

IEEE

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Enhancing Personalization and Mitigating Inter-Patient Variability in Continuous Blood Glucose Prediction Using Multi-Task Deep LSTMs;2024 IEEE International Symposium on Medical Measurements and Applications (MeMeA);2024-06-26

2. An intelligent diabetes classification and perception framework based on ensemble and deep learning method;PeerJ Computer Science;2024-03-29

3. Integrating self-powered medical devices with advanced energy harvesting: A review;Energy Strategy Reviews;2024-03

4. Unraveling the Potential of Heart Rate Variability for Type 1 Diabetes Prediction;2023 International Workshop on Biomedical Applications, Technologies and Sensors (BATS);2023-09-28

5. Ensemble Methods of Machine Learning Algorithms for Early Diabetic Detection in Comparison;2023 1st International Conference on Circuits, Power and Intelligent Systems (CCPIS);2023-09-01

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