Toward a Multimodal Multitask Model for Neurodegenerative Diseases Diagnosis and Progression Prediction

Sofia Lahrichi, Maryem Rhanoui, Mounia Mikram, Bouchra El Asri

2021

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.

Paper Citation

in Harvard Style

Lahrichi S., Rhanoui M., Mikram M. and El Asri B. (2021). Toward a Multimodal Multitask Model for Neurodegenerative Diseases Diagnosis and Progression Prediction. In Proceedings of the 10th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-521-0, pages 322-328. DOI: 10.5220/0010600003220328

in Bibtex Style

@conference{data21,
author={Sofia Lahrichi and Maryem Rhanoui and Mounia Mikram and Bouchra El Asri},
title={Toward a Multimodal Multitask Model for Neurodegenerative Diseases Diagnosis and Progression Prediction},
booktitle={Proceedings of the 10th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2021},
pages={322-328},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010600003220328},
isbn={978-989-758-521-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - Toward a Multimodal Multitask Model for Neurodegenerative Diseases Diagnosis and Progression Prediction
SN - 978-989-758-521-0
AU - Lahrichi S.
AU - Rhanoui M.
AU - Mikram M.
AU - El Asri B.
PY - 2021
SP - 322
EP - 328
DO - 10.5220/0010600003220328