Medical Images Dataset

Our research focuses on enhancing medical image classification by optimizing a CNN-SVM hybrid model using an improved Grey Wolf Optimizer (GWO). While CNNs excel at feature extraction, they often face challenges in handling complex medical images efficiently. To address this, our study integrates SVM for classification and fine-tunes model parameters using an enhanced GWO. The approach is tested on four diverse datasets—Brain Tumor Database (BTD), Chest Pneumothorax Dataset (CPD), Gastrointestinal Cancer Dataset (GCD), and ISIC 2019 Skin Lesion Dataset (SLD)—covering MRI, X-ray, endoscopic, and dermatoscopic imaging. Performance evaluation using multiple metrics demonstrates the model’s effectiveness, achieving high accuracy across all datasets.