Branchial Cleft Anomalies, Dermoid and Epidermoid Cysts, Infantile Hemangiomas, Neck Mass, Teratomas, Thyroglossal Duct Cysts
Conditions
Brief 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.
Detailed 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.
Interventions
DIAGNOSTIC_TESTArtificial Intelligence Algorithm
Different machine learning and deep learning computer aided strategies for model construction and validation.
Sponsors
West China Hospital
Study design
Observational model
COHORT
Time perspective
OTHER
Eligibility
Sex/Gender
ALL
Age
0 Years to 18 Years
Healthy volunteers
No
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| The diagnostic accuracy of neck masses with AI-based screening tools in children | 1 month | The diagnostic accuracy of neck masses with AI-based screening tools in children. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| The diagnostic positive predictive value of neck masses with AI-based screening tools in children | 1 month | The diagnostic positive predictive value 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 | The diagnostic sensitivity 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 | The diagnostic specificity 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 | The diagnostic negative predictive value of neck masses with AI-based screening tools in children |
Countries
China
Contacts
Primary ContactYuhan Yang, MD
Outcome results
None listed