Oral Cancer Detection Through Machine Learning Algorithm: An Investigation

Cancer is a disease that affects different organs of our body, including the blood, lungs, and mouth. Tumours composed of infectious cells form in the tissues of the specific part, causing injury to it. To treat cancer, it is critical to diagnose it early on, as prevention is preferable to treatment. Currently, cancer detection and diagnosis typically include a biopsy, in which tissues from the tumour are histologically processed to determine whether cancer is present or not. Other approaches for detecting cancer include scanning with computerised tomography, magnetic resonance imaging, and other imaging modalities, all of which pose a risk to the development of malignant cells in the body. This study seeks to detect cancer in the human body's buccal cavity using machine learning, convolutional neural networks (CNN), and the AlexNet and ResNet algorithms. This study also attempts to demonstrate that the method utilised outperforms existing machine learning algorithms in terms of execution time and accuracy.