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

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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Bibliographic Details
Main Authors: Chuang Xi, Ruiqi Du, Ren Wang, Yang Wang, Liying Hou, Mengqi Luan, Xuan Zheng, Hongyan Huang, Zhixin Liang, Xuehai Ding, Quanyong Luo, Chentian Shen
Format: Article
Language:English
Published: Wiley 2023-04-01
Series:View
Subjects:
BRAFV600E mutation
deep learning
thyroid cancer
thyroid nodule
ultrasound
Online Access:https://doi.org/10.1002/VIW.20220057

Internet

https://doi.org/10.1002/VIW.20220057

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