Abstract:The incidence of thyroid cancer has been increasing, and early diagnosis and treatment are crucial for improving patient prognosis. With the advancement of artificial intelligence (AI) technology, significant progress has been made in its application in the diagnosis and treatment of thyroid cancer. AI technology has notably enhanced the diagnostic accuracy of thyroid cancer. By optimizing imaging examinations such as ultrasound and CT scans, it can more precisely identify malignant features of thyroid nodules. In fine-needle aspiration biopsy, the integration of AI with genetic testing technologies has improved both the accuracy and efficiency of diagnosis. In terms of treatment, AI assists in intraoperative functional preservation, reducing the risk of surgical trauma. For instance, it can accurately identify the locations of the recurrent laryngeal nerve and parathyroid glands. Additionally, AI is capable of predicting the efficacy of 131I treatment and the risk of complications, thereby guiding postoperative follow-up and management. The core strength of AI technology lies in its powerful data processing and analytical capabilities, enabling it to uncover latent patterns within data and provide a scientific basis for treatment decision-making. Looking ahead, with continuous technological advancements, AI is expected to propel the diagnosis and treatment of thyroid cancer towards greater intelligence and precision. However, challenges such as data privacy and algorithm transparency need to be addressed. This article provides a review of the research progress of AI technology in the fields of diagnosis, treatment, and prognosis prediction of thyroid cancer, explores the current strengths and weaknesses of AI technology, and looks forward to its future development directions while acknowledging challenges like data privacy and algorithm transparency.