Oral Cancer Detection using Deep Learning Techniques
Nagamani Tenali, Vasavi Sripriya Desu, Charishma Boppa, Varshith Chowdary Chintala, Bhavana Guntupalli
Abstract
One of the most serious tumors that affects the oral cavity is oral cancer. Smoking cigarettes and increased tobacco use are the main risk factors for mouth cancer. When oral cancer is found in its early stages and treated successfully, many lives can be saved Histological analysis of an oral cavity tissue sample is the accepted method in medicine for identifying oral cancer. This method requires more time and is more invasive than obtaining a brush sample and then performing a cytological analysis. For a better prognosis, treatment plan, and chance of survival, early diagnosis is essential. Therefore, this paper suggests deep learning techniques to perform early detection of oral cancer and eventually leads to its prevention. Deep learning techniques enable early detection of disease to provide precision medicine. According to the recent research reports, this method has significantly advanced the extraction of data and interpretation of crucial information related to medical imaging. It has the potential to identify oral cancer with a cost-efficient, non-invasive, and effective method, having substantial clinical implications.