Thyroid cancer, the most prevalent endocrine cancer, has gained significant global attention due to its impact on public health. Extensive research efforts have been dedicated to leveraging artificial intelligence (AI) methods for the early detection of this disease, aiming to reduce its morbidity rates. However, a comprehensive understanding of the structured organization of research applications in this particular field remains elusive. To address this knowledge gap, we conducted a systematic review and developed a comprehensive taxonomy of machine learning-based applications in thyroid cancer pathogenesis, diagnosis, and prognosis. Our primary objective was to facilitate the research community's ability to stay abreast of technological advancements and potentially lead the emerging trends in this field. This survey presents a coherent literature review framework for interpreting the advanced techniques used in thyroid cancer research. A total of 758 related studies were identified and scrutinized. To the best of our knowledge, this is the first review that provides an in-depth analysis of the various aspects of AI applications employed in the context of thyroid cancer. Furthermore, we highlight key challenges encountered in this domain and propose future research opportunities for those interested in studying the latest trends or exploring less-investigated aspects of thyroid cancer research. By presenting this comprehensive review and taxonomy, we contribute to the existing knowledge in the field, while providing valuable insights for researchers, clinicians, and stakeholders in advancing the understanding and management of this disease.

翻译：甲状腺癌作为最常见的内分泌恶性肿瘤，因其对公共健康的影响而受到全球广泛关注。大量研究致力于应用人工智能方法实现该疾病的早期检测，以期降低其发病率。然而，对于该领域研究应用的结构化组织方式仍缺乏系统性认知。为弥补这一知识缺口，我们开展了系统性文献综述，构建了基于机器学习的甲状腺癌发病机制、诊断与预后应用的完整分类体系。本研究的主要目标是帮助研究界及时把握技术发展动态，并引领该领域新兴趋势。本综述提出了一个连贯的文献分析框架，用于阐释甲状腺癌研究中的先进技术。共识别并详细审查了758项相关研究。据我们所知，这是首篇对甲状腺癌领域人工智能应用的多维度进行深度分析的综述。此外，我们指出了该领域面临的关键挑战，并为关注最新趋势或探索未充分研究方面的学者提出了未来研究方向。通过呈现这一系统综述与分类体系，我们既丰富了现有知识储备，也为研究人员、临床医生及利益相关者推进该疾病认知与管理提供了重要见解。