Back Cover: AI‐BRAFV600E: A deep convolutional neural network for BRAFV600E mutation status prediction of thyroid nodules using ultrasound images (View 2/2023). Issue 2 (24th April 2023)
- Record Type:
- Journal Article
- Title:
- Back Cover: AI‐BRAFV600E: A deep convolutional neural network for BRAFV600E mutation status prediction of thyroid nodules using ultrasound images (View 2/2023). Issue 2 (24th April 2023)
- Main Title:
- Back Cover: AI‐BRAFV600E: A deep convolutional neural network for BRAFV600E mutation status prediction of thyroid nodules using ultrasound images (View 2/2023)
- Authors:
- Xi, Chuang
Du, Ruiqi
Wang, Ren
Wang, Yang
Hou, Liying
Luan, Mengqi
Zheng, Xuan
Huang, Hongyan
Liang, Zhixin
Ding, Xuehai
Luo, Quanyong
Shen, Chentian - Abstract:
- Abstract : 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.
- Is Part Of:
- View. Volume 4:Issue 2(2023)
- Journal:
- View
- Issue:
- Volume 4:Issue 2(2023)
- Issue Display:
- Volume 4, Issue 2 (2023)
- Year:
- 2023
- Volume:
- 4
- Issue:
- 2
- Issue Sort Value:
- 2023-0004-0002-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2023-04-24
- Subjects:
- Drug delivery systems -- Periodicals
Bioengineering -- Periodicals
Bioinformatics -- Periodicals
Biomedical materials -- Periodicals
681.761 - Journal URLs:
- https://onlinelibrary.wiley.com/journal/2688268x# ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/viw2.283 ↗
- Languages:
- English
- ISSNs:
- 2688-3988
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 27026.xml