58 citations · 181 across the 29 of their papers we have counts for
3 papers · 1 filter
MMSE-Calibrated Few-Shot Prompting for Alzheimer's Detection
Jana Sweidan, Mounim A. El-Yacoubi, Nasredine Semmar
Prompting large language models is a training-free method for detecting Alzheimer's disease from speech transcripts. Using the ADReSS dataset, we revisit zero-shot prompting and st…
Interpreting Deep Glucose Predictive Models for Diabetic People Using RETAIN
Maxime De Bois, Mounîm A. El Yacoubi, Mehdi Ammi
Progress in the biomedical field through the use of deep learning is hindered by the lack of interpretability of the models. In this paper, we study the RETAIN architecture for the…
Enhancing the Interpretability of Deep Models in Heathcare Through Attention: Application to Glucose Forecasting for Diabetic People
Maxime De Bois, Mounîm A. El Yacoubi, Mehdi Ammi
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 forecasting for diabe…