Hybrid Intelligent Diagnosis
Bhargavi Maridu, R. Renugadevi, Syed Shareefunnisa, Sajida Sultana Sk · Advances in medical technologies and clinical practice book series · 2024
The chapter presents a novel approach in medical diagnostics, focusing on differentiating oligodendroglioma and astrocytoma through a hybrid intelligent system. This method integrates deep learning with radiology and pathology imaging to enhance tumor diagnosis. Convolutional neural networks (CNNs) analyze MRI and CT scans alongside microscopic slides, providing a comprehensive understanding of tumors. By leveraging both radiology and pathology, this method offers a precise diagnostic tool, with a significant improvement in accuracy compared to traditional methods. Especially effective in complex cases, our approach showcases the potential of hybrid intelligent systems for accurate, efficient, and automated diagnostics, not only in brain tumor diagnosis but across medical imaging and diagnostics in general.