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Deep Learning-Assisted Ultrasonic Diagnosis and Localization of Testicular Appendix Torsion

NCT07301086 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 2000

Last updated 2025-12-31

No results posted yet for this study

Summary

Ultrasound data were both retrospectively and prospectively collected from the primary center and six other sub-centers. Combined with clinical diagnostic outcomes, the data labeling was completed by physicians with extensive clinical experience. In this study, ConvNeXtV2 was used as the classification network and YOLOv12 was adopted as the detection network.The retrospective dataset from the primary center was split into training, validation, and test subsets, on which the model was trained, validated, and tested respectively; additional validation was conducted on both retrospective and prospective datasets from the primary center and sub-centers.Meanwhile, four physicians were assigned to interpret the ultrasound data from the retrospective and prospective datasets from the primary center and sub-centers using two diagnostic methods-independent diagnosis and artificial intelligence (AI)-assisted diagnosis-and the diagnostic accuracy of these two approaches was further compared.By collecting and learning the treatment methods of patients in the primary center training set, predicting the treatment methods of patients in the sub-center datasets, and comparing the proportion of surgeries predicted by AI with the actual proportion of surgeries, the efficacy of the model was verified.

Conditions

  • Testicular Appendix Torsion
  • Testicular Torsion
  • Epididymitis

Sponsors & Collaborators

  • Ying Jiang

    lead OTHER

Principal Investigators

  • Jingjing Ye, Phd Degree · Zhejiang University School of Medicine Children's Hospital

Eligibility

Min Age
1 Minute
Max Age
18 Years
Sex
MALE
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2026-01-31
Primary Completion
2026-05-31
Completion
2026-05-31

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07301086 on ClinicalTrials.gov