Back Cover: AI‐BRAFV600E: A deep convolutional neural network for BRAFV600E mutation status prediction of thyroid nodules using ultrasound images (View 2/2023)

The back cover image describes a DCNN model based on ultrasound images to predict the BRAFV600E mutation in thyroid nodules which achieved encouraging predictive performance in the test sets from four hospitals (AUC 0.84–0.93). This model might provide a non‐invasive and convenient method for predic...

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Veröffentlicht in:View (Beijing, China) China), 2023-04, Vol.4 (2), p.n/a
Hauptverfasser: Xi, Chuang, Du, Ruiqi, Wang, Ren, Wang, Yang, Hou, Liying, Luan, Mengqi, Zheng, Xuan, Huang, Hongyan, Liang, Zhixin, Ding, Xuehai, Luo, Quanyong, Shen, Chentian
Format: Artikel
Sprache:eng
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Zusammenfassung:The back cover image describes a DCNN model based on ultrasound images to predict the BRAFV600E mutation in thyroid nodules which achieved encouraging predictive performance in the test sets from four hospitals (AUC 0.84–0.93). This model might provide a non‐invasive and convenient method for predicting the BRAFV600E mutation to assist clinicians to select more appropriate management for patients with thyroid nodules or thyroid cancer.
ISSN:2688-3988
2688-268X
DOI:10.1002/viw2.283