人工智能在甲状腺细胞病理学诊断中的研究进展

Research advances in artificial intelligence in cytopathologic diagnosis of thyroid

  • 摘要: 甲状腺癌的发病率呈逐年上升趋势,超声引导下细针穿刺是相对简便、微创、准确的诊断方法。近年来,人工智能在众多医学领域广泛应用,显著提高了疾病诊断的效率和准确性。本文结合当前人工智能在甲状腺细胞病理学诊断中的最新研究文献,对人工智能在甲状腺细胞病理学诊断中的应用现状进行综述,分析人工智能应用于甲状腺细胞病理学所面临的困难和挑战,并对其未来的应用前景进行展望。

     

    Abstract: The incidence of thyroid cancer is increasing year by year, ultrasound-guided fine needle puncture is a relatively simple, minimally invasive, and highly accurate diagnostic method. In recent years, artificial intelligence (AI) has been widely used in many medical fields, significantly improving the efficiency and accuracy of disease diagnosis. This paper focuses on the latest literature on the application of AI in thyroid cytopathological diagnosis, reviews the research status, analyzes the difficulties and challenges faced by AI in thyroid cytopathology, and points out the future application prospects of AI in thyroid cytopathology.

     

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