Leveraging Quantum-Based Architectures for Robust Diagnostics

ArXi:2511.12386v2 Announce Type: replace Quantum machine learning has emerged as a promising approach for medical image analysis, particularly in settings where compact models and expressive feature representations are desired. This paper presents a hybrid classical--quantum diagnostic framework that integrates dataset-specific preprocessing, transfer learning, and quantum convolutional neural networks (QCNNs) for multi-class medical image classification.