The Clinical Application of Artificial Intelligence Assisted Renal Biopsy Diagnosis System.
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age15-79
SponsorZhujiang Hospital
About this trial
This research project aims to collect images from patients with chronic glomerulonephritis. For each subject, the images obtained from renal biopsy will undergo evaluation by both the diagnostic model and the 'gold standard' diagnosis by pathologists. The researchers will test the subjects using the diagnostic model and compare the results with the known 'gold standard' diagnosis, in order to evaluate the AUC, specificity, and sensitivity of the diagnostic model.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Voluntary signing of informed consent form;
Patients clinically diagnosed or suspected of having chronic kidney disease according to the 2023 KDIGO Clinical Practice Guideline for the Evaluation and Management of Kidney Disease;
Undergoing renal biopsy and pathological specimen preparation.
Disqualifiers
Biopsy tissue from donor kidney or transplanted kidney;
Poor quality of pathological specimen, unable to conduct pathological diagnosis.
Trial population
For patients with chronic kidney disease who need further diagnosis through renal biopsy.
Trial design
Design model
Other
Time perspective
Prospective
Treatments tested in this trial
Not listed
Trial groups
No trial groups listed
Trial outcomes
Primary outcomes
1
The area under curve (AUC) of Receiver Operating Characteristic (ROC) curves of the TEM-AID artificial intelligence model
The area under curve (AUC) of Receiver Operating Characteristic (ROC) curves of the TEM-AID artificial intelligence model for candidates will be calculated.
Time frame
baselineSecondary outcomes
1
The specificity of the TEM-AID artificial intelligence model.
The specificity of the TEM-AID artificial intelligence model for candidates will be calculated.
Time frame
baseline2
The sensitivity of the TEM-AID artificial intelligence model.
The sensitivity of the TEM-AID artificial intelligence model for candidates will be calculated.
Time frame
baselineSponsors and contacts
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Source ClinicalTrials.gov