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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT05187923
Other study ID # HX-20211023
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date January 1, 2021
Est. completion date December 31, 2024

Study information

Verified date January 2022
Source West China Hospital
Contact Yuhan Yang, MD
Phone 8613258389785
Email yyh_1023@163.com
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial 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.


Recruitment information / eligibility

Status Recruiting
Enrollment 1500
Est. completion date December 31, 2024
Est. primary completion date December 31, 2024
Accepts healthy volunteers No
Gender All
Age group N/A to 18 Years
Eligibility 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

Study Design


Intervention

Diagnostic Test:
Artificial Intelligence Algorithm
Different machine learning and deep learning computer aided strategies for model construction and validation.

Locations

Country Name City State
China West China Hospital, Sichuan University Chengdu Sichuan

Sponsors (1)

Lead Sponsor Collaborator
West China Hospital

Country where clinical trial is conducted

China, 

Outcome

Type Measure Description Time frame Safety issue
Primary The diagnostic accuracy of neck masses with AI-based screening tools in children The diagnostic accuracy of neck masses with AI-based screening tools in children. 1 month
Secondary The diagnostic sensitivity of neck masses with AI-based screening tools in children The diagnostic sensitivity of neck masses with AI-based screening tools in children. 1 month
Secondary The diagnostic specificity of neck masses with AI-based screening tools in children The diagnostic specificity of neck masses with AI-based screening tools in children. 1 month
Secondary The diagnostic positive predictive value of neck masses with AI-based screening tools in children The diagnostic positive predictive value of neck masses with AI-based screening tools in children. 1 month
Secondary The diagnostic negative predictive value of neck masses with AI-based screening tools in children The diagnostic negative predictive value of neck masses with AI-based screening tools in children 1 month
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