医学
甲状腺结节
危险分层
结核(地质)
甲状腺
甲状腺癌
放射科
超声波
内科学
生物
古生物学
作者
Nydia Burgos,Naykky Singh Ospina,Jennifer A. Sipos
标识
DOI:10.1016/j.ecl.2021.12.002
摘要
Clinical evidence supports the association of ultrasound features with benign or malignant thyroid nodules and serves as the basis for sonographic stratification of thyroid nodules, according to an estimated thyroid cancer risk. Contemporary guidelines recommend management strategies according to thyroid cancer risk, thyroid nodule size, and the clinical scenario. Yet, reproducible and accurate thyroid nodule risk stratification requires expertise, time, and understanding of the weight different ultrasound features have on thyroid cancer risk. The application of artificial intelligence to overcome these limitations is promising and has the potential to improve the care of patients with thyroid nodules.
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