Machine Learning and Deep Learning Approaches for Early Alzheimer’s Detection in Patients with Subjective Cognitive Decline: A Systematic Literature Review

Zyad Taouil, Nourhène Ben Rabah, Bénédicte Le Grand

2025

Abstract

This paper investigates the application of machine learning and deep learning techniques for the early detection of Alzheimer’s Disease (AD) in patients with Subjective Cognitive Decline (SCD), a preclinical AD stage. Traditional diagnosis methods struggle to detect AD at this stage, making ML a promising alternative for early intervention. A systematic literature review (SLR) was conducted to identify and analyze the most effective ML models, data types, and preprocessing techniques for early AD detection. This review highlights that Convolutional Neural Network (CNN), Random Forest, and logistic regression models, particularly when applied to multimodal data (e.g., neuroimaging, genetic, and vocal features), showing high diagnosis accuracy. Data preprocessing steps such as feature engineering and data augmentation significantly enhance model performance. This paper also explores the practical implications of implementing ML models in clinical settings and discusses system integration, clinician training, and ethical considerations surrounding patient data. This research emphasizes the potential of ML to enhance early AD diagnosis.

Paper Citation

in Harvard Style

Taouil Z., Ben Rabah N. and Grand B. (2025). Machine Learning and Deep Learning Approaches for Early Alzheimer’s Detection in Patients with Subjective Cognitive Decline: A Systematic Literature Review. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 598-610. DOI: 10.5220/0013247600003890

in Bibtex Style

@conference{icaart25,
author={Zyad Taouil and Nourhène Ben Rabah and Bénédicte Grand},
title={Machine Learning and Deep Learning Approaches for Early Alzheimer’s Detection in Patients with Subjective Cognitive Decline: A Systematic Literature Review},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2025},
pages={598-610},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013247600003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Machine Learning and Deep Learning Approaches for Early Alzheimer’s Detection in Patients with Subjective Cognitive Decline: A Systematic Literature Review
SN - 978-989-758-737-5
AU - Taouil Z.
AU - Ben Rabah N.
AU - Grand B.
PY - 2025
SP - 598
EP - 610
DO - 10.5220/0013247600003890
PB - SciTePress