Construction and Efficacy Evaluation of the Integrated Prediction Model of Chinese and Western Medicine for Early Chronic Kidney Disease -- Based on Artificial Intelligence Algorithm
Phase 1
Not yet recruiting
- Conditions
- chronic kidney disease
- Registration Number
- ITMCTR2000003891
- Lead Sponsor
- Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Pending
- Sex
- All
- Target Recruitment
- Not specified
Inclusion Criteria
1. Adults over the age of 18;
2. Ability to read and understand words, and be able to communicate in language;
3. Volunteer for this experiment.
Exclusion Criteria
1. People with cognitive dysfunction or mental disorders;
2. Serious functional or organic diseases;
3. Patients who have undergone renal replacement therapy.
Study & Design
- Study Type
- Screening
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method
- Secondary Outcome Measures
Name Time Method
Related Research Topics
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What molecular pathways or biomarkers does the AI model integrate for early CKD prediction?
How does the AI model's predictive accuracy compare to standard-of-care diagnostics for early CKD?
Which biomarkers are used in the AI model to identify high-risk patients for early CKD?
What are the potential limitations or adverse outcomes of using AI models in CKD screening?
What combination therapies for early CKD are validated by AI models integrating TCM and Western medicine?