Cytological Classification Diagnosis for Thyroid Nodules via Multimodal Model Deep Learning.

ABSTRACT: The rising prevalence of thyroid nodules is straining limited cytopathology resources, resulting in excessive overdiagnosis and overtreatment with significant patient and healthcare consequences. To address this, AI-TFNA is developed, a robust artificial intelligence platform leveraging extensive clinical data to enhance diagnostic accuracy and clinical efficiency. A total of 20,803 thyroid samples are collected from seven medical centers across different regions in China. Of these, 4,421 thyroid fine-needle aspiration (TFNA) samples from three hospitals are used to train AI-TFNA, ensuring strong generalizability across diverse clinical settings. For the internal validation, AI-TFNA demonstrates exceptional performance: the overall accuracy of TBS I is 93.27%, the sensitivity of TBS V and

SUBMITTER: Lou Y 

PROVIDER: S-EPMC12752556 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature