Adult Diffuse Nephropathy
Conditions
Interventions
Index test:Establish multiple deep learning models for predicting diffuse nephropathy 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
18 Years to 75 Years
Inclusion criteria
Inclusion criteria: 1. Case group (diffuse kidney disease group): (1) Aged 18–75 years; (2) Complete clinical data; (3) Good-quality ultrasound images available for analysis; (4) Pathologically confirmed by renal biopsy as one of the following: IgA nephropathy, membranous nephropathy, focal segmental glomerulosclerosis, lupus nephritis, etc. 2. Healthy control group: (1) Aged 18–75 years; (2) Complete clinical data; (3) Good-quality ultrasound images available for analysis; (4) Normal renal function (normal serum creatinine and eGFR) and normal urinalysis.
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;
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Area Under Curve;Positive Predictive Value;Sensitivity;Specificity;Negative Predictive Value; | — |
Countries
China
Contacts
Public ContactZou Chunpeng
The Second Affiliated Hospital of Wenzhou Medical University
Outcome results
None listed