Using AI to Diagnose and Predict Diseases from Health Records and Imaging Data
AI-Agent Assisted Automation for Diagnosing and Predicting Patients Using Electronic Health Records and Multimodal Data
This study is testing whether an AI tool can help doctors diagnose and predict diseases better by looking at patients' health records and medical images.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 2000000 (estimated) |
| Sex | All |
| Sponsor | The Eye Hospital of Wenzhou Medical University Academic / other |
| Locations | 6 sites (Guangzhou, Guangdong and 5 other locations) |
| Trial ID | NCT06791499 on ClinicalTrials.gov |
What this trial studies
This observational study evaluates the effectiveness of an AI agent designed to assist in diagnosing and predicting diseases by analyzing electronic health records (EHR) and multimodal imaging data. The AI agent employs advanced machine learning algorithms to process diverse health data sources, aiming to enhance the accuracy of medical diagnoses and predictions. By comparing the AI's performance with traditional diagnostic methods, the study seeks to determine its potential benefits in clinical decision-making. Participants will provide historical health data, which will be analyzed by the AI to generate diagnostic suggestions and predictions without requiring additional interventions.
Who should consider this trial
Good fit: Ideal candidates include individuals with comprehensive electronic health records and relevant multimodal imaging data who have a confirmed diagnosis of one or more diseases.
Not a fit: Patients with ambiguous or unverifiable diagnoses or those with duplicate health records may not benefit from this study.
Why it matters
Potential benefit: If successful, this AI-driven approach could significantly improve diagnostic accuracy and optimize treatment strategies for patients.
How similar studies have performed: Other studies utilizing AI for diagnostic purposes have shown promising results, indicating potential for success in this approach.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Participants must have comprehensive electronic health records (EHR) available, including demographic information, medical history, and laboratory results. 2. Participants must have available multimodal imaging data (e.g., X-rays, CT scans, MRIs, ultrasounds) relevant to their health condition. 3. Participants must have a confirmed diagnosis of one or more diseases or health conditions based on clinical records or imaging data. 4. Patients must provide consent for the use of their historical health data for research purposes. Exclusion Criteria: 1. Participants with ambiguous or unverifiable diagnoses that cannot be accurately categorized. 2. Duplicate or redundant patient data (e.g., repeated records of the same patient without clear differentiation).
Where this trial is running
Guangzhou, Guangdong and 5 other locations
- Nanfang Hospital — Guangzhou, Guangdong, China (Recruiting)
- Sun Yat-Sen Memorial Hospital — Guangzhou, Guangdong, China (Recruiting)
- Sun Yat-sen University Cancer Hospital — Guangzhou, Guangdong, China (Recruiting)
- West China Hospital — Chengdu, Sichuan, China (Recruiting)
- First Affiliated Hospital of Wenzhou Medical University — Wenzhou, Zhejiang, China (Recruiting)
- Second Affiliated Hospital of Wenzhou Medical University — Wenzhou, Zhejiang, China (Recruiting)
Study contacts
- Study coordinator: Fei Liu, MD
- Email: liufei_2359@163.com
- Phone: +86 13810512704
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.