Computer Aided Tool for Diagnosis of Neck Masses in Children

  • STATUS
    Recruiting
  • End date
    Dec 31, 2024
  • participants needed
    1500
  • sponsor
    West China Hospital
Updated on 24 March 2022

Summary

The aim of this study was to evaluate the diagnostic efficacy of computer aided diagnostic tool for neck masses using machine learning and deep learning techniques on clinical information and radiological images in children.

Description

This study is a retrospective-prospective design by West China Hospital, Sichuan University, including clinical data and radiological images. A retrospective database was enrolled for patients with definite histological diagnosis and available radiological images from June 2010 and December 2020. The investigators have constructed deep learning and machine learning diagnostic models on this retrospective cohort and validated it internally. A prospective cohort would recruit patients found neck masses since January 2021. The proposed computer aided diagnostic models would also be validated in this prospective cohort externally. The aim of this study was to evaluate the diagnostic efficacy of computer aided diagnostic tool for neck masses using machine learning and deep learning techniques on clinical data and radiological images in children.

Details
Condition Neck Mass, Thyroglossal Duct Cysts, Branchial Cleft Anomalies, Dermoid and Epidermoid Cysts, Infantile Hemangiomas, Teratomas
Treatment Artificial intelligence algorithm
Clinical Study IdentifierNCT05187923
SponsorWest China Hospital
Last Modified on24 March 2022

Eligibility

Yes No Not Sure

Inclusion Criteria

Age up to 18 years old
Receiving no treatment before diagnosis
With written informed consent

Exclusion Criteria

Clinical data missing
Unavailable radiological images
Without written informed consent
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