Application and Evaluation of Vision-LSTM Model in Diagnostic Ultrasound Imaging of TI-RADS Class 4b Thyroid Nodules
Application and Evaluation of Vision-LSTM Model in Diagnostic Ultrasound Imaging of TI-RADS Class 4b Thyroid Nodules
The aim of this study was to evaluate the performance of artificial intelligence (AI) technology in the diagnosis of thyroid nodules, specifically in the field of ultrasound image analysis. It focuses on the accuracy and clinical feasibility of the AI system based on the Vision-LSTM model in the diagnosis of TI-RADS category 4b thyroid nodules.
Inclusion Criteria:(1) Patients with thyroid nodules visible on ultrasound who underwent biopsy and/or surgical resection. (2) Diagnosed as TI-RADS category 4b on the basis of preoperative ultrasound images by two sonographers with more than 5 years of experience in thyroid ultrasound diagnosis. (3) All nodules underwent puncture biopsy or surgery to obtain pathologic results.
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Exclusion Criteria:(1)The quality of the patient's ultrasound images was poor. (2) The patient has incomplete clinical and imaging data. (3) The patient has had thyroid surgery or other treatment.
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