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Lecture notes in networks and systems

A Hybrid Classical-Quantum Machine Learning for the Binary Classification of Medical Images

Felipe Guicharrousse, Mauricio Solar

Published Jan 1, 2026• 0 citations
Publisher
DOI
10.1007/978-3-032-26217-2_19

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This research presents a hybrid quantum-classical machine learning framework for medical image classification under noisy conditions using chest X-ray images. A classical Convolutional Neural Network (CNN) model and a hybrid quantum-classical model integrating variational quantum circuits were implemented using PyTorch and PennyLane. Gaussian noise was introduced during validation to evaluate model robustness under image perturbations. Experimental results demonstrated comparable performance between the classical CNN and the hybrid quantum-classical model, highlighting the potential of Quantum Machine Learning (QML) for future healthcare AI applications. GitHub Repository:https://github.com/saichandukundarapu/quantum-covid-detection
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