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Simple Summary: The amount of diagnosed thyroid nodules increases every year. Many researchers have tried to optimize the process of classifying and diagnosing thyroid nodules using artificial intelligence. The aim of this study was to assess the latest applications of artificial intelligence in diagnosing and classifying thyroid nodules. The focus was on innovations in the use of artificial intelligence in the field of ultrasonography and microscopic diagnosis, although other applications were reviewed as well. In total, we analyzed 930 papers published from 2018 to 2022. The incidence of thyroid nodules diagnosed is increasing every year, leading to a greater risk of unnecessary procedures being performed or wrong diagnoses being made. In our paper, we present the latest knowledge on the use of artificial intelligence in diagnosing and classifying thyroid nodules. We particularly focus on the usefulness of artificial intelligence in ultrasonography for the diagnosis and characterization of pathology, as these are the two most developed fields. In our search of the latest innovations, we reviewed only the latest publications of specific types published from 2018 to 2022. We analyzed 930 papers in total, from which we selected 33 that were the most relevant to the topic of our work. In conclusion, there is great scope for the use of artificial intelligence in future thyroid nodule classification and diagnosis. In addition to the most typical uses of artificial intelligence in cancer differentiation, we identified several other novel applications of artificial intelligence during our review. [ABSTRACT FROM AUTHOR]