Toward a multimodal multitask model for neurodegenerative diseases diagnosis and progression prediction

• URL: http://arxiv.org/abs/2110.09309v1
• Date: Sun, 10 Oct 2021 11:44:16 GMT
• Title: Toward a multimodal multitask model for neurodegenerative diseases diagnosis and progression prediction
• Authors: Sofia Lahrichi and Maryem Rhanoui and Mounia Mikram and Bouchra El Asri
• Abstract summary: This article overviews various categories of models used for Alzheimer's disease prediction with their respective learning methods. It establishes a comparative study of early prediction and detection Alzheimer's disease progression. Finally, a robust and precise detection model is proposed.
• Score: 0.5735035463793008
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Recent studies on modelling the progression of Alzheimer's disease use a single modality for their predictions while ignoring the time dimension. However, the nature of patient data is heterogeneous and time dependent which requires models that value these factors in order to achieve a reliable diagnosis, as well as making it possible to track and detect changes in the progression of patients' condition at an early stage. This article overviews various categories of models used for Alzheimer's disease prediction with their respective learning methods, by establishing a comparative study of early prediction and detection Alzheimer's disease progression. Finally, a robust and precise detection model is proposed.

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