Medical Images Dataset

Our research focuses on enhancing medical image classification by optimizing a <b>CNN-SVM hybrid model</b> using an improved <b>Grey Wolf Optimizer (GWO)</b>. 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—<b>Brain Tumor Database (BTD), Chest Pneumothorax Dataset (CPD), Gastrointestinal Cancer Dataset (GCD), and ISIC 2019 Skin Lesion Dataset (SLD)</b>—covering MRI, X-ray, endoscopic, and dermatoscopic imaging. Performance evaluation using multiple metrics demonstrates the model’s effectiveness, achieving high accuracy across all datasets.