This paper summarizes the research progress of artificial intelligence technology in ultrasonic diagnosis of thyroid nodule. In recent years

the incidence of thyroid cancer is on the rise

and thyroid screening is included in routine physical examination

which increases the clinical workload. Oversensitive and oversensitive. Although pathological diagnosis is the gold standard

not all lesions need to be removed at the same time. FNA can effectively improve the accuracy of diagnosis

develop individual diagnosis and treatment

and avoid over-diagnosis. Ultrasound

as the first choice in the diagnosis of thyroid lesions

can effectively find the lesions and preliminarily judge the biological behavior of the lesions. It is convenient and effective

and has unique diagnostic advantages

but it has a certain operator dependence. The development of artificial intelligence provides a "second opinion" for clinical work and becomes a "third eye" for doctors

assisting doctors to find lesions

improving the accuracy of diagnosis and reducing the diagnosis deviation caused by human factors. Although the diagnostic ability of CAD system based on DL is comparable to that of experienced physicians to a certain extent

it lacks transparency and interpretability

and still has a long way to go in information security.