About this document
Deep Learning for Jaw Tumor Diagnosis by Đăng Khoa is a document available to read on EtoBox.
This study presents a deep learning-based method for diagnosing cysts and tumors of the jaw using a two-branch network trained on a large dataset of healthy and lesion samples. The proposed method achieved an average classification accuracy of 88.72% and improved performance when distinguishing between lesion and healthy samples. The approach emphasizes explainability and reliability, providing a diagnostic tool that aids in the accurate identification of jaw tumors and cysts.
- Author
- Đăng Khoa
- Language
- EN