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AI-Driven Prediction of Biological Age With EHR
Sponsor: The Eye Hospital of Wenzhou Medical University
Summary
This is a multi-center, retrospective clinical study designed to evaluate the application and effectiveness of an AI-assisted predictive model for predicting biological age using electronic health records (EHR). The study will analyze various health data points, including medical history, laboratory results, and clinical observations, to estimate the biological age of patients. By comparing biological age with chronological age, the study aims to assess the accuracy of the model and its potential in identifying age-related health risks and improving patient care.
Official title: Predicting Biological Age Using Electronic Health Records: An AI-Based Approach
Key Details
Gender
All
Age Range
0 Years - 100 Years
Study Type
OBSERVATIONAL
Enrollment
1000000
Start Date
2023-03-01
Completion Date
2025-04-02
Last Updated
2025-04-02
Healthy Volunteers
Yes
Conditions
Interventions
AI-assisted predictive model
This study utilizes an AI-assisted predictive model that analyzes multimodal data from electronic health records, including medical history, laboratory results, imaging data, and lifestyle factors, to estimate biological age. The model employs deep learning algorithms to predict biological age, compare it to chronological age, and identify early signs of age-related health risks. The intervention is not a direct treatment or procedure but aims to develop a tool for predicting biological age to help personalize care and improve long-term health outcomes.
Locations (4)
Nanfang Hospital
Guangzhou, Guangdong, China
First Affiliated Hospital of Wenzhou Medical University
Wenzhou, Zhejiang, China
Second Affiliated Hospital of Wenzhou Medical University
Wenzhou, Zhejiang, China
The Eye Hospital of Wenzhou Medical University
Wenzhou, Zhejiang, China