Leveraging Deep Q-Network Agents with Dynamic Routing Mechanisms in Convolutional Neural Networks for Enhanced and Reliable Classification of Alzheimer’s Disease from MRI Scans

Jolanta Podolszanska

2025

Abstract

With limited data and complex image structures, accurate classification of medical images remains a significant challenge in AI-assisted diagnostics. This study presents a hybrid CNN model with a capsule network layer and dynamic routing mechanism, enhanced with a Deep Q-network (DQN) agent, for MRI image classification in Alzheimer’s disease detection. The approach combines a capsule network that captures complex spatial patterns with dynamic routing, improving model adaptability. The DQN agent manages the weights and optimizes learning by interacting with the evolving environment. Experiments conducted on popular MRI datasets show that the model outperforms traditional methods, significantly improving classification accuracy and reducing misclassification rates. These results suggest that the approach has great potential for clinical applications, contributing to the accuracy and reliability of automated diagnostic systems.

Paper Citation

in Harvard Style

Podolszanska J. (2025). Leveraging Deep Q-Network Agents with Dynamic Routing Mechanisms in Convolutional Neural Networks for Enhanced and Reliable Classification of Alzheimer’s Disease from MRI Scans. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 1172-1179. DOI: 10.5220/0013301900003890

in Bibtex Style

@conference{icaart25,
author={Jolanta Podolszanska},
title={Leveraging Deep Q-Network Agents with Dynamic Routing Mechanisms in Convolutional Neural Networks for Enhanced and Reliable Classification of Alzheimer’s Disease from MRI Scans},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={1172-1179},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013301900003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Leveraging Deep Q-Network Agents with Dynamic Routing Mechanisms in Convolutional Neural Networks for Enhanced and Reliable Classification of Alzheimer’s Disease from MRI Scans
SN - 978-989-758-737-5
AU - Podolszanska J.
PY - 2025
SP - 1172
EP - 1179
DO - 10.5220/0013301900003890
PB - SciTePress