Artificial intelligence–assisted digital thyroid FNA cytology: Improved agreement and sensitivity for higher‐risk Bethesda categories with enhanced screening efficiency

Abstract

Accurate cytologic classification of thyroid nodules is essential for clinical management, but interobserver variability and indeterminate interpretations remain persistent challenges. The clinical feasibility of AIxTHY, a disease‐specific deep‐learning algorithm integrated into a digital cytology platform, was evaluated for assisting thyroid fine‐needle aspiration (FNA) diagnosis using whole‐slide imaging (WSI).