A New Neural Network Model for Prediction Next Stage of Alzheimer’s Disease

Nour Zawawi, Nour Zawawi, Heba Saber, Mohamed Hashem, Tarek Gharib

2022

Abstract

Alzheimer’s disease (AD) is a brain-related illness; The risk of development is minimized when diagnosed early. The early detection and treatment of Alzheimer’s disease are crucial since they can decrease disease progression, improve symptom management, allow patients to receive timely guidance and support, and save money on healthcare. Regrettably, much current research focuses on characterizing illness states in their current phases rather than forecasting disease development. Because Alzheimer’s disease generally progresses in phases over time, we believe that analyzing time-sequential data can help with disease prediction. Long short-term memory (LSTM) is a recurrent neural network that links previous input to the current task. A new Alzheimer’s Disease Random Forest (RF) LSTM Prediction Model (RFLSTM-PM) is proposed to capture the conditions between characteristics and the next stage of Alzheimer’s Disease after noticing that a patient’s data could be beneficial in predicting disease progression. Experiments reveal that our approach beats most existing models and can help with early-onset AD prediction. Furthermore, tests show that it can recognize disease- related brain regions across multiple data modalities (Magnetic resonance imaging (MRI), Neurological Test). Also, it showed decreased value in Mean Absolute Error and Root Mean Square Error for forecasting the progression of the disease.

Paper Citation

in Harvard Style

Zawawi N., Saber H., Hashem M. and Gharib T. (2022). A New Neural Network Model for Prediction Next Stage of Alzheimer’s Disease. In Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-549-4, pages 689-696. DOI: 10.5220/0010892400003122

in Bibtex Style

@conference{icpram22,
author={Nour Zawawi and Heba Saber and Mohamed Hashem and Tarek Gharib},
title={A New Neural Network Model for Prediction Next Stage of Alzheimer’s Disease},
booktitle={Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2022},
pages={689-696},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010892400003122},
isbn={978-989-758-549-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - A New Neural Network Model for Prediction Next Stage of Alzheimer’s Disease
SN - 978-989-758-549-4
AU - Zawawi N.
AU - Saber H.
AU - Hashem M.
AU - Gharib T.
PY - 2022
SP - 689
EP - 696
DO - 10.5220/0010892400003122