Hybrid Classical-Quantum (HCQ) Alzheimer's Classification via Supervised $\beta$-VAE and Quantum Kernels
arXiv:2606.14194v1 Announce Type: cross Abstract: This paper presents a two-stage Hybrid Classical-Quantum (HCQ) pipeline for binary Alzheimer's disease (AD) classification from 3D T1-weighted structural MRI volumes, where the classical and quantum components are designed to complement each other rather than operate independently. A supervised 3D $\beta$-variational autoencoder (VAE) is trained end-to-end under voxel-wise reconstruction, KL-divergence, and focal classification losses that compress each 3D MRI volume (resized from 152 x 184 x 152 to 96 x 96 x 96) into a 64-dimensional latent co
The advancements in quantum computing research and AI development are maturing, enabling the exploration of synergistic applications in complex domains like medical diagnostics, specifically Alzheimer's classification.
This development indicates a tangible path towards integrating quantum computing with classical AI for real-world, high-impact medical applications, potentially revolutionizing diagnostic accuracy and early detection for neurodegenerative diseases.
The computational paradigm for medical image analysis is shifting to include hybrid quantum-classical approaches, offering new methods for feature extraction and classification previously inaccessible to purely classical techniques.
- · Quantum computing hardware developers
- · AI healthcare solution providers
- · Medical imaging diagnostics
- · Patients with neurodegenerative diseases
- · Traditional medical diagnostic methods
- · AI models relying solely on classical architectures for complex pattern recognit
Improved early detection rates and accuracy for Alzheimer's disease via hybrid quantum-classical models.
Accelerated development and adoption of quantum machine learning techniques across various medical and scientific fields.
Enhanced understanding of complex biological data leading to new therapeutic strategies and personalized medicine fueled by quantum-assisted AI.
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