NCT06258044

The Application Value of Deep Learning-Based Nomograms in Benign-Malignant Discrimination of TI-RADS Category 4 Thyroid Nodules

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 500 (actual)
• Sponsor: Ma Zhe · Academic / Other
• Sex: All
• Age: 23 Years – 78 Years
• Healthy volunteers: Not accepted

Summary

This retrospective study focuses on benign and malignant classification of thyroid nodules using deep learning techniques and evaluates the value of deep learning based nomograms in the classification of TI-RADS category 4 thyroid nodules to improve the accuracy of benign and malignant identification of TI-RADS category 4 thyroid nodules. Materials and methods: Patients who visited in The First Affiliated Hospital of Shandong First Medical University ＆ Shandong Provincial Qianfoshan Hospital were collected. Their general clinical features, information on preoperative ultrasound diagnosis, and postoperative pathologic data were reviewed.

Conditions

• Thyroid Nodule

Timeline

• Start date: 2022-04-01
• Primary completion: 2023-11-30
• Completion: 2023-11-30
• First posted: 2024-02-14
• Last updated: 2024-02-14

Locations

1 site across 1 country: China