全球甲状腺癌的发病率持续上升，主要影响女性。尽管死亡率稳定，但甲状腺癌的独特特征需要采取不同的方法。多数病例由分化型甲状腺癌组成，可以通过标准治疗方法如甲状腺切除术和放射性碘治疗有效管理。然而，罕见的变种如间受体癌则需要专门的干预，通常采用靶向治疗。虽然这些药物专注于症状管理，但并非治愈性药物。本综述文章深入探讨了甲状腺癌的基本调控因子，包括遗传、表观遗传和非编码RNA因子，并探讨了它们之间的复杂相互作用和影响。表观遗传修饰会直接影响诱因基因的表达，而长非编码RNA会影响微小RNA的功能和表达，最终导致肿瘤发生。 此外，本文对甲状腺癌药物治疗和非药物治疗的优缺点进行了简明总结。此外，在技术进步的推动下，将现代软件和计算机技术融入医疗实践日益普遍。人工智能和机器学习技术有潜力预测治疗结果、分析数据，并开发个体化的治疗方法以满足患者的特异性需求。在甲状腺癌领域，先进的机器学习和深度学习技术可以分析肿瘤超声结果和细针穿刺活检样本等因素，为未来提供更准确、更有效的治疗模式。版权所有 © 2023 作者。由Elsevier Inc.出版。保留所有权利。

Thyroid cancer continues to exhibit a rising incidence globally, predominantly affecting women. Despite stable mortality rates, the unique characteristics of thyroid carcinoma warrant a distinct approach. Differentiated thyroid cancer, comprising most cases, is effectively managed through standard treatments such as thyroidectomy and radioiodine therapy. However, rarer variants, including anaplastic thyroid carcinoma, necessitate specialized interventions, often employing targeted therapies. Although these drugs focus on symptom management, they are not curative. This review delves into the fundamental modulators of thyroid cancers, encompassing genetic, epigenetic, and non-coding RNA factors while exploring their intricate interplay and influence. Epigenetic modifications directly affect the expression of causal genes, while long non-coding RNAs impact the function and expression of micro-RNAs, culminating in tumorigenesis. Additionally, this article provides a concise overview of the advantages and disadvantages associated with pharmacological and non-pharmacological therapeutic interventions in thyroid cancer. Furthermore, with technological advancements, integrating modern software and computing into healthcare and medical practices has become increasingly prevalent. Artificial intelligence and machine learning techniques hold the potential to predict treatment outcomes, analyze data, and develop personalized therapeutic approaches catering to patient specificity. In thyroid cancer, cutting-edge machine learning and deep learning technologies analyze factors such as ultrasonography results for tumor textures and biopsy samples from fine needle aspirations, paving the way for a more accurate and effective therapeutic landscape in the near future.Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.