Sep 8, 2020 · In this paper, we explore the RETAIN architecture for the task of glusose forecasting for diabetic people.
In this paper, we explore the RETAIN architecture for the task of glucose forecasting for diabetic people. By using a two-level attention mechanism, the ...
The adoption of deep learning in healthcare is hindered by their "black box" nature. In this paper, we explore the RETAIN architecture for the task of glusose ...
Enhancing the Interpretability of Deep Models in Heathcare Through Attention: Application to Glucose Forecasting for Diabetic People · 3 Citations · 31 References.
Interpretability is very important in healthcare fields and especially in glucose prediction. Indeed, it allows the patient to make more informed decisions ...
Sep 16, 2021 · By using a two-level attention mechanism, the recurrent-neural-network-based RETAIN model is interpretable.
May 16, 2024 · In this paper, we study the RETAIN architecture for the forecasting of future glucose values for diabetic people. Thanks to its two-level ...
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Jul 2, 2024 · We propose KCCAM_DNN, a diabetes prediction method that integrates Kendall's correlation coefficient and an attention mechanism within a deep neural network.
We propose a multi-source adversarial transfer learning framework that enables the learning of a feature representation that is similar across the sources.
Jul 18, 2024 · Our machine learning model predicts poor glycemic control (HbA 1c ≥8%) using the transformer architecture, incorporating an attention mechanism.