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RECRUITING
NCT05847894

Assisting Pulmonary Disease Diagnosis With Ophthalmic Artificial Intelligence Technology

Sponsor: Zhongshan Ophthalmic Center, Sun Yat-sen University

View on ClinicalTrials.gov

Summary

This study intends to collect ophthalmologic examination results, pulmonary examination results and related indexes from patients with pulmonary disease and control populations, and combine big data analysis and artificial intelligence technology to explore whether new methods can be provided for early screening strategies for pulmonary disease with the aid of ophthalmologic examination, and thus assist in identifying the types of pulmonary disease and determining disease prognosis.

Key Details

Gender

All

Age Range

Any - Any

Study Type

OBSERVATIONAL

Enrollment

10000

Start Date

2020-06-29

Completion Date

2026-05

Last Updated

2025-05-23

Healthy Volunteers

Yes

Interventions

DIAGNOSTIC_TEST

Ophthalmic examination

Various ophthalmic examination modalities, including slit lamp photography, fundus photography, optical coherence tomography imaging and optical coherence tomography angiography, etc.

DIAGNOSTIC_TEST

Pulmonary Examination

Various pulmonary examination modalities, including radiography, chest CT, pulmonary function measurement, etc.

Locations (4)

Zhongshan Ophthalmic Center, Sun Yat-sen University

Guangzhou, Guangdong, China

Guangzhou Kindness Health Care Center (Guangzhou Jiubang Shanxin Clinic Ltd)

Guangzhou, Guangdong, China

the First Affiliated Hospital of Guangzhou Medical University

Guangzhou, Guangdong, China

Shenzhen Third People's Hospital

Shenzhen, Guangdong, China