Using AI to predict biological age from health records
Official title: Predicting Biological Age Using Electronic Health Records: An AI-Based Approach
Run by The Eye Hospital of Wenzhou Medical University · NCT06791486 · Data updated 2026-11-12
This study is testing if an AI tool can use health records to predict a person's biological age and help identify health risks for better patient care.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 0 Years to 100 Years |
| Sex | All |
| Enrollment | 1000000 (estimated) |
| Sponsor | The Eye Hospital of Wenzhou Medical University Academic / other |
| Locations | 4 sites (Guangzhou, Guangdong and 3 other locations) |
| Status | Recruiting |
| Started | March 1, 2023 |
| Main results expected | April 2, 2025 |
| Study ends | April 2, 2025 |
| Registry record updated | April 2, 2025 |
| Trial ID | NCT06791486 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates include patients with comprehensive EHR data and no significant cognitive impairments.
✕Probably not a fit
Patients with incomplete EHR data or severe cognitive disorders may not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study evaluates the effectiveness of an AI-assisted predictive model to estimate biological age using electronic health records (EHR). By analyzing various health data points, including medical history and laboratory results, the study aims to compare biological age with chronological age to assess the model's accuracy. The goal is to identify age-related health risks and improve patient care through personalized healthcare strategies. This multi-center approach integrates diverse patient data to enhance diagnostic accuracy and optimize clinical workflows.
Why it matters
Potential benefit: If successful, this study could lead to improved identification of age-related health risks and more personalized healthcare interventions.
How similar studies have gone: While the application of AI in predicting biological age is a novel approach, similar studies have shown promise in enhancing predictive accuracy in healthcare.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Patients with comprehensive and accessible EHR data, including medical history, laboratory results, treatment data, imaging data (if available), and lifestyle factors (e.g., smoking, physical activity, diet). 2. Patients with no significant cognitive impairments that would prevent them from providing informed consent or participating in the study. 3. All participants must provide informed consent for the use of their medical data for research purposes. Exclusion Criteria: 1. Patients with incomplete or missing critical EHR data such as medical history, laboratory results, or treatment data that are necessary for predicting biological age. 2. atients with severe cognitive disorders (e.g., dementia, significant mental disabilities) who are unable to provide informed consent or participate meaningfully in the study. 3. Patients with terminal illnesses or those with limited life expectancy where biological age predictions may not be relevant for the purposes of the study.
Where it's running
-
Nanfang Hospital
Guangzhou, Guangdong, China Recruiting -
First Affiliated Hospital of Wenzhou Medical University
Wenzhou, Zhejiang, China Recruiting -
Second Affiliated Hospital of Wenzhou Medical University
Wenzhou, Zhejiang, China Recruiting -
The Eye Hospital of Wenzhou Medical University
Wenzhou, Zhejiang, China Recruiting
Study contacts
- Study coordinator: Fei Liu, MD
- Email: liufei_2359@163.com
- Phone: +86 13810512704
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.