NCT04413370

Dry Eye Screening and Referral System

The Development of Artificial Intelligence Dry Eye Screening and Referral System

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 518 (actual)
• Sponsor: Sun Yat-sen University · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Accepted

Summary

Dry eye is one of the most common ocular surface diseases. Its pathogenic factors are related to multiple etiology. Because of the complexity of the pathogenesis of dry eye, the diversity of related examinations, and the inconsistency of symptoms and signs of dry eye patients, the diagnosis of dry eye has higher requirements on the professional technology and examination equipment of ophthalmologists. The purpose of this study is to establish a case-control cohort of dry eye patients. Multimodal data will be collected from participants, including medical history information, ocular surface disease index scale (OSDI), anterior segment photography, and treatment outcome of dry eye patients. The correlation between the characteristics of anterior segment images and dry eye diagnosis will be explored by artificial intelligence algorithms. The purpose of this study was to develop an artificial intelligence dry eye screening and referral system.

Conditions

• Dry Eye

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	Dry eye diagnostic test	The artificial intelligent dry eye screening platform

Timeline

• Start date: 2020-01-06
• Primary completion: 2022-04-19
• Completion: 2022-08-01
• First posted: 2020-06-02
• Last updated: 2022-04-25

Locations

1 site across 1 country: China