Diagnosis of Thyroid Nodule Malignancy Using Peritumoral Region and Artificial Intelligence
The proposed AI model trained on nodule+the peripheral region performed optimally in external validations and outperformed the radiologists using the ATA and TI-RADS guidelines.
Authors
- Selda Behestani (ORCID: https://orcid.org/0000-0003-0810-5870)
- Mohammad Mirza‐Aghazadeh‐Attari (ORCID: https://orcid.org/0000-0001-7927-6912)
- Afshin Mohammadi (ORCID: https://orcid.org/0000-0002-9557-3359)
- Ali Abbasian Ardakani (ORCID: https://orcid.org/0000-0001-7536-0973)
- Chai Hong Yeong (ORCID: https://orcid.org/0000-0003-1572-4143)
- Aik Hao Ng (ORCID: https://orcid.org/0000-0002-3260-2749)
- Wei Lin Ng (ORCID: https://orcid.org/0000-0003-1589-9824)
- U. Rajendra Acharya (ORCID: https://orcid.org/0000-0003-2689-8552)
- Kasturi Nair Tangaraju
- Revathy Suresh
Institutions
- Johns Hopkins University (US)
- University of Southern Queensland (AU)
- University of Malaya (MY)
- Urmia University (IR)
- National Cancer Institute (MY)
- Taylor's University (MY)
- University of Kuala Lumpur (MY)
- Shahid Beheshti University of Medical Sciences (IR)
Publication Details
- Journal
- Journal of Ultrasound in Medicine
- Published
- 2025-02-15
- DOI
- https://doi.org/10.1002/jum.16665
- Citations
- 5
- Primary Topic
- Thyroid Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 6.47