AI-Driven Prediction of Biological Age With EHR

RecruitingOBSERVATIONAL
Enrollment

1,000,000

Participants

Timeline

Start Date

March 1, 2023

Primary Completion Date

April 2, 2025

Study Completion Date

April 2, 2025

Conditions
Biological Age
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.

Trial Locations (4)

Unknown

RECRUITING

Nanfang Hospital, Guangzhou

RECRUITING

First Affiliated Hospital of Wenzhou Medical University, Wenzhou

RECRUITING

Second Affiliated Hospital of Wenzhou Medical University, Wenzhou

RECRUITING

The Eye Hospital of Wenzhou Medical University, Wenzhou

All Listed Sponsors
lead

The Eye Hospital of Wenzhou Medical University

OTHER