pediatric glomerulonephritis
Conditions
Interventions
Gold Standard:renal biospy
Index test:Establish multiple deep learning models for predicting glomerulonephritis based on ultrasound images, including ResNet network model, Inception network model, DenseNet network model, etc.
Sponsors
The Second Affiliated Hospital of Wenzhou Medical University
Eligibility
Sex/Gender
All
Age
No minimum to 18 Years
Inclusion criteria
Inclusion criteria: 1. Complete clinical data; 2. Good quality of ultrasound images; 3. Having undergone renal biopsy;
Exclusion criteria
Exclusion criteria: 1. A history of previous renal surgery; 2. A history of previous radiotherapy and chemotherapy; 3. Presence of congenital renal diseases, such as polycystic kidney disease, horseshoe kidney, duplicated kidney, etc; 4. Suboptimal ultrasound image quality that affects diagnosis;
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| sensitivity;specificity;positive predictive value;kidney size;negative predictive value;AUROCs; | — |
Countries
China
Contacts
Public ContactZou Chunpeng
The Second Affiliated Hospital of Wenzhou Medical University
Outcome results
None listed