Using AI to predict genetic information from health records
Predicting Patient Genotypes Using Electronic Health Records and Multimodal Data Through AI-Based Models
This study is testing whether an AI can use your health records to predict your genetic information without needing any genetic tests.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 100000 (estimated) |
| Sex | All |
| Sponsor | The Eye Hospital of Wenzhou Medical University Academic / other |
| Locations | 4 sites (Guangzhou, Guangdong and 3 other locations) |
| Trial ID | NCT06791421 on ClinicalTrials.gov |
What this trial studies
This observational study aims to evaluate the effectiveness of an AI-based model that predicts a patient's genotype by analyzing electronic health records (EHR) and multimodal data, including lab results and imaging. The study will utilize historical medical data to train the AI system, which will then compare its predictions against actual genetic testing results. By eliminating the need for direct genetic testing, this approach seeks to provide a non-invasive and cost-effective method for genotype prediction, potentially enhancing personalized medicine and early disease diagnosis. Participants will not undergo genetic testing; instead, their existing health data will be leveraged for analysis.
Who should consider this trial
Good fit: Ideal candidates are individuals with comprehensive electronic health records, including medical history, lab results, and imaging data.
Not a fit: Patients without available health records or those with ambiguous genetic testing results may not benefit from this study.
Why it matters
Potential benefit: If successful, this study could provide a non-invasive and cost-effective tool for predicting genetic information, improving personalized medicine and early disease diagnosis.
How similar studies have performed: While the use of AI in healthcare is growing, this specific approach of predicting genotype from non-genetic data is relatively novel and has not been extensively tested.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Participants must have comprehensive electronic health records (EHR), including medical history, lab results, and relevant imaging data (e.g., X-rays, MRIs, CT scans). 2. Participants must have existing genetic testing data available for comparison, if applicable. 3. Participants must be willing to provide consent for the use of their health data in the study. 4. Participants must have no active intervention related to genetic testing or prediction during the study period. 5. Participants should have complete and verifiable health data to allow for accurate prediction by the AI model. Exclusion Criteria: 1. Participants without available EHR, lab results, or imaging data. 2. Participants with ambiguous, inaccurate, or unverifiable genetic testing results that cannot be used for comparison. 3. Patients with significant discrepancies or missing data that would prevent the AI model from making accurate predictions.
Where this trial is running
Guangzhou, Guangdong and 3 other locations
- Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University — Guangzhou, Guangdong, China (Recruiting)
- Sun Yat-sen University Cancer Hospital — Guangzhou, Guangdong, China (Recruiting)
- First Affiliated Hospital of Wenzhou Medical University — Wenzhou, Zhejiang, China (Completed)
- 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.