Research Progress on the Prediction of BRAF Gene Mutation in Papillary Thyroid Carcinoma by Artificial Intelligence Combined with Medical Imaging

The global incidence of papillary thyroid carcinoma has been exhibiting an upward trend, with the BRAF gene serving as a specific molecular marker that is closely associated with the aggressiveness and lymph node metastasis of this malignancy. In recent years, radiomics and deep learning methodologies based on medical imaging have emerged as innovative approaches for predicting molecular markers, enabling the extraction of subvisual information that transcends human perceptual capabilities. These advanced techniques provide novel predictive tools for identifying BRAF gene mutations in papillary thyroid carcinoma. This article aims to comprehensively review the applications and research advancements of machine learning and deep learning approaches based on medical imaging in predicting BRAF gene mutations in papillary thyroid carcinoma.