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RECRUITING
NCT06791486

AI-Driven Prediction of Biological Age With EHR

Sponsor: The Eye Hospital of Wenzhou Medical University

View on ClinicalTrials.gov

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

OTHER

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