<ul><li>Researchers propose a hybrid classical quantum convolutional neural network (CQ CNN) for Alzheimer's Disease (AD) detection using 3D MRI.</li><li>The CQ CNN incorporates quantum machine learning techniques, specifically parameterized quantum circuits (PQCs), with classical machine learning architectures.</li><li>The proposed CQ CNN achieves higher accuracy in fewer epochs compared to classical models, with a 97.50% accuracy using only 13K parameters.</li><li>The use of diffusion-generated data, along with real samples, represents a notable first in the field of quantum machine learning for AD detection.</li></ul>

CQ CNN: A Hybrid Classical Quantum Convolutional Neural Network for Alzheimer's Disease Detection Using Diffusion Generated and U Net Segmented 3D MRI

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