208 citations
- M. Ammi7
- Maxime De Bois2 profiles7 · h 1
- Mounîm A. El-Yacoubi6 · h 23
- Joaquín García2 profiles5 · h 24
- Andrea Araldo4 profiles4 · h 6
- R. Douc4 · h 28
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- Frédéric Petitpont3
- Jérôme Boudy3
- Marius Preda2 profiles3 · h 6
- Institut Polytechnique de ParisFR60 papers
- Centre National de la Recherche ScientifiqueFR23 papers
- Services répartis, Architectures, MOdélisation, Validation, Administration des RéseauxFR16 papers
- Institut Mines-TélécomFR10 papers
- Télécom ParisFR9 papers
- Laboratoire Traitement et Communication de l’InformationFR8 papers
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- Université Paris-SaclayFR7 papers
- École Nationale Supérieure d’Informatique pour l’Industrie et l’EntrepriseFR4 papers
- Laboratoire d'Informatique pour la Mécanique et les Sciences de l'IngénieurFR4 papers
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Showing q-bio.QMShow all
3 papers · 1 filter
q-bio.QM2020★ 6 cited
Integration of Clinical Criteria into the Training of Deep Models: Application to Glucose Prediction for Diabetic People
Maxime De Bois, Mounîm A. El Yacoubi, Mehdi Ammi
Standard objective functions used during the training of neural-network-based predictive models do not consider clinical criteria, leading to models that are not necessarily clinic…
q-bio.QM2020★ 6 cited
Model Fusion to Enhance the Clinical Acceptability of Long-Term Glucose Predictions
Maxime De Bois, Mounîm A. El Yacoubi, Mehdi Ammi
This paper presents the Derivatives Combination Predictor (DCP), a novel model fusion algorithm for making long-term glucose predictions for diabetic people. First, using the histo…
q-bio.QM2020★ 13 cited
Study of Short-Term Personalized Glucose Predictive Models on Type-1 Diabetic Children
Maxime De Bois, Mounîm A. El Yacoubi, Mehdi Ammi
Research in diabetes, especially when it comes to building data-driven models to forecast future glucose values, is hindered by the sensitive nature of the data. Because researcher…