Develop a hybrid quantum-classical deep learning system for ...

Prompt

Develop a hybrid quantum-classical deep learning system for detecting and classifying pulmonary diseases, including Pneumonia, Tuberculosis, and COVID-19, using chest X-ray and CT scan images. The system uses pretrained ResNet50 as a classical feature extractor to capture complex medical image patterns. Extracted 2048-dimensional features are reduced using PCA and encoded into a quantum circuit. A Variational Quantum Classifier (VQC) processes these features for final classification into Normal, Pneumonia, TB, and COVID-19 classes. Compare the hybrid model with classical ResNet50, SVM, Random Forest, and CNN models using accuracy, precision, recall, F1-score, sensitivity, specificity, AUC, computational efficiency, and explainability metrics.