AI‐BRAFV600E: A deep convolutional neural network for BRAFV600E mutation status prediction of thyroid nodules using ultrasound images

Background: The BRAFV600E mutation is a valuable indicator for thyroid cancer diagnosis. This study aimed to develop a deep convolutional neural network (DCNN) model based on ultrasound images to predict the BRAFV600E mutation status of thyroid nodules. Methods: The ultrasound images were obtained f...

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Библиографические подробности

Главные авторы:	Chuang Xi, Ruiqi Du, Ren Wang, Yang Wang, Liying Hou, Mengqi Luan, Xuan Zheng, Hongyan Huang, Zhixin Liang, Xuehai Ding, Quanyong Luo, Chentian Shen
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Wiley 2023-04-01
Серии:	View
Предметы:	BRAFV600E mutation deep learning thyroid cancer thyroid nodule ultrasound
Online-ссылка:	https://doi.org/10.1002/VIW.20220057
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