Deep Learning-Based Continuous Glucose Monitoring with Diabetic Prediction Using Deep Spectral Recurrent Neural Network
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-5166-6_33
Reference20 articles.
1. Wang J, Bai Y, Xia B (2020) Simultaneous diagnosis of severity and features of diabetic retinopathy in fundus photography using deep learning. IEEE J Biomed Health Inform 24(12)
2. Estonilo CG, Festijo ED (2021) Development of deep learning-based mobile application for predicting diabetes mellitus. In: 2021 4th international conference of computer and informatics engineering (IC2IE), pp 13–18
3. Xu L, He J, Hu Y (2021) Early diabetes risk prediction based on deep learning methods. In: 2021 4th international conference on pattern recognition and artificial intelligence (PRAI), pp 282–286
4. Kumar L, Johri P (2022) Designing a health care application for prediction diabetes using LSTM, SVM and deep learning. In: 2022 2nd international conference on advance computing and innovative technologies in engineering (ICACITE), pp 1319–1323
5. Miazi ZA et al (2021) A cloud-based app for early detection of type II diabetes with the aid of deep learning. In: 2021 international conference on automation, control and mechatronics for Industry 4.0 (ACMI), pp 1–6
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