NCT05847894

Assisting Pulmonary Disease Diagnosis With Ophthalmic Artificial Intelligence Technology

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 10,000 (estimated)
• Sponsor: Zhongshan Ophthalmic Center, Sun Yat-sen University · Academic / Other
• Sex: All
• Age: —
• Healthy volunteers: Accepted

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.

Conditions

• Pulmonary Diseases
• Ophthalmological Diagnostic Techniques
• Artificial Intelligence

Interventions

Type	Name	Description
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.

Timeline

• Start date: 2020-06-29
• Primary completion: 2026-05-01
• Completion: 2026-05-01
• First posted: 2023-05-08
• Last updated: 2025-05-23

Locations

4 sites across 1 country: China