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Maxime De Bois
Maxime De Bois
PhD Student, Université Paris-Saclay, LIMSI, France
Verified email at limsi.fr - Homepage
Title
Cited by
Cited by
Year
Adversarial multi-source transfer learning in healthcare: Application to glucose prediction for diabetic people
M De Bois, MA El Yacoubi, M Ammi
Computer Methods and Programs in Biomedicine 199, 105874, 2021
172021
Study of short-term personalized glucose predictive models on type-1 diabetic children
M De Bois, MA El Yacoubi, M Ammi
2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019
102019
Prediction-coherent LSTM-based recurrent neural network for safer glucose predictions in diabetic people
MD Bois, MAE Yacoubi, M Ammi
International Conference on Neural Information Processing, 510-521, 2019
62019
GLYFE: review and benchmark of personalized glucose predictive models in type 1 diabetes
M De Bois, MAE Yacoubi, M Ammi
Medical & Biological Engineering & Computing, 1-17, 2021
32021
Enhancing the Interpretability of Deep Models in Healthcare Through Attention: Application to Glucose Forecasting for Diabetic People
M De Bois, MA El Yacoubi, M Ammi
International Journal of Pattern Recognition and Artificial Intelligence 35 …, 2021
22021
Interpreting deep glucose predictive models for diabetic people using retain
MD Bois, MA El Yacoubi, M Ammi
International Conference on Pattern Recognition and Artificial Intelligence …, 2020
22020
Model fusion to enhance the clinical acceptability of long-term glucose predictions
M De Bois, M Ammi, MA El Yacoubi
2019 IEEE 19th International Conference on Bioinformatics and Bioengineering …, 2019
22019
Energy expenditure estimation through daily activity recognition using a smart-phone
M De Bois, H Amroun, M Ammi
2018 IEEE 4th World Forum on Internet of Things (WF-IoT), 167-172, 2018
22018
Integration of clinical criteria into the training of deep models: Application to glucose prediction for diabetic people
M De Bois, MA El-Yacoubi, M Ammi
Smart Health 21, 100193, 2021
2021
Apprentissage profond sous contraintes biomédicales pour la prédiction de la glycémie future de patients diabétiques
M De Bois
Université Paris-Saclay, 2020
2020
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