Investigation of S-Detect AI (a computer-aided diagnosis tool) versus ultrasound operators for thyroid nodule classification using British Thyroid Association guidelines: A pilot diagnostic accuracy study
- DOI
- 10.1177/1742271x261479402
- Published
- 2026-09-03
- Container
- Ultrasound
- Publisher
- SAGE Publications
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1177/1742271x261479402,
title = {Investigation of S-Detect AI (a computer-aided diagnosis tool) versus ultrasound operators for thyroid nodule classification using British Thyroid Association guidelines: A pilot diagnostic accuracy study},
author = {Kieran Walker and James Michael and Mark Ballard and Geoffrey Chilvers and Steve Colley and Khalid Hussain and Lloyd Rickard},
year = {2026},
journal = {Ultrasound},
doi = {10.1177/1742271x261479402},
url = {https://doi.org/10.1177/1742271x261479402}
}RIS
TY - JOUR TI - Investigation of S-Detect AI (a computer-aided diagnosis tool) versus ultrasound operators for thyroid nodule classification using British Thyroid Association guidelines: A pilot diagnostic accuracy study AU - Kieran Walker AU - James Michael AU - Mark Ballard AU - Geoffrey Chilvers AU - Steve Colley AU - Khalid Hussain AU - Lloyd Rickard PY - 2026 JO - Ultrasound DO - 10.1177/1742271x261479402 UR - https://doi.org/10.1177/1742271x261479402 ER -
APA
Walker, K., Michael, J., Ballard, M., Chilvers, G., Colley, S., Hussain, K., & Rickard, L. (2026). Investigation of S-Detect AI (a computer-aided diagnosis tool) versus ultrasound operators for thyroid nodule classification using British Thyroid Association guidelines: A pilot diagnostic accuracy study. Ultrasound. https://doi.org/10.1177/1742271x261479402
Source records
- crossref · retrieved 2026-09-26T13:31:53.622Z