Investigation of artificial intelligence–based clinical decision support system’s performance in reducing the fine needle aspiration rate of thyroid nodules: A pilot study
Artificial intelligence can improve specificity without significantly compromising sensitivity. There was a suggested reduction in the fine needle aspiration rate, in the histologically proven benign nodules, by 53%. This had no statistical significance, likely due to the small population, however, it is thought to be the largest study to date. Further investigation with wider-ranging studies is suggested.
Authors
- Heather Venables (ORCID: https://orcid.org/0000-0002-9388-9771)
- Vincent K. Lam (ORCID: https://orcid.org/0000-0002-1319-2588)
- A. R. BARNES
- Rebecca White (ORCID: https://orcid.org/0000-0002-7662-4026)
- Ram Vaidhyanath (ORCID: https://orcid.org/0009-0007-7475-7371)
Institutions
- University of Derby (GB)
- University Hospitals of Leicester NHS Trust (GB)
Publication Details
- Journal
- Ultrasound
- Published
- 2024-12-07
- DOI
- https://doi.org/10.1177/1742271x241299220
- Citations
- 1
- Primary Topic
- Thyroid Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.36
Funders
- University of Derby
- University Hospitals of Leicester NHS Trust