Construction Of an Oral Cancer Auto-Classify system Based On Machine-Learning for Artificial Intelligence

Meng-Jia Lian, Chih-Ling Huang, Tzer-Min Lee
2019 9th International Conference on Computer Science, Engineering and Applications (CCSEA 2019)   unpublished
Oral cancer is one of the most widespread tumors of the head and neck region. An earlier diagnosis can help dentist getting a better therapy plan, giving patients a better treatment and the reliable techniques for detecting oral cancer cells are urgently required. This study proposes an optic and automation method using reflection images obtained with scanned laser pico-projection system, and Gray-Level Co-occurrence Matrix for sampling. Moreover, the artificial intelligence technology, Support
more » ... Vector Machine, was used to classify samples. Normal Oral Keratinocyte and dysplastic oral keratinocyte were simulating the evolvement of cancer to be classified. The accuracy in distinguishing two cells has reached 85.22%. Compared to existing diagnosis methods, the proposed method possesses many advantages, including a lower cost, a larger sample size, an instant, a non-invasive, and a more reliable diagnostic performance. As a result, it provides a highly promising solution for the early diagnosis of oral squamous carcinoma.
doi:10.5121/csit.2019.90903 fatcat:fp3tlcxjizgsdbrigajs6ph55q