Detection of oral cancer using deep learning approach
| Autor: | B C Kavitha, G R Reshma, S B Manoj Kumar, K B Naveen, M B Anandaraju |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | International journal of health sciences. :8429-8436 |
| ISSN: | 2550-696X 2550-6978 |
| DOI: | 10.53730/ijhs.v6ns4.10584 |
| Popis: | Globally, oral cancer is becoming more and more of an issue, and in some nations, like Taiwan, India, and Sri Lanka, it is at the very top of the list. Tobacco, alcohol, and betel nut use are responsible for more than 95% of all mouth cancer cases (BQ). In Western nations, smoking and alcohol consumption are the two biggest risk factors, but in Asian nations, smoking and BQ usage are the two most risk factors. It is alarming how frequently people with advanced oral cancer arrive. The best method for minimising personal illness burden, lowering morbidity and mortality, and enhancing quality of life. The detection, evaluation, and treatment of oral cancer remain challenges for the dental profession. In the proposed approach, deep learning algorithm has been used to simulate the development of cancer diagnosis and therapy, and they are successful in predicting future outcomes of a cancer. For the best outcomes in the detection and diagnosis of oral cancer, an effective deep learning and feature selection approach utilising Alex net model has been applied.Overall, 500 images with different resolution were used in our system. |
| Databáze: | OpenAIRE |
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