Artificial intelligence-enhanced ultrasound imaging for thyroid nodule detection and malignancy classification: a study on YOLOv11.

ABSTRACT:

Background

Thyroid nodules are a common clinical concern, with accurate diagnosis being critical for effective treatment and improved patient outcomes. Traditional ultrasound examinations rely heavily on the physician's experience, which can lead to diagnostic variability. The integration of artificial intelligence (AI) into medical imaging offers a promising solution for enhancing diagnostic accuracy and efficiency. This study aimed to evaluate the effectiveness of the You Only Look Once v. 11 (YOLOv11) model in detecting and classifying thyroid nodules through ultrasound images, with the goal of supporting real-time clinical decision-making and improving diagnostic workflows.

Methods

We used the YOLOv11 model to analyze a dataset of 1,503 thyroid ultrasound images, divided

SUBMITTER: Yang J 

PROVIDER: S-EPMC12397667 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature