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Evaluate the performance of artificial intelligence in the diagnosis and treatment recommendations of dry eye syndrome

Research on the Application of Large Language Models in the Diagnosis and Treatment Decision-making of Dry Eye Patients

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500111755
Enrollment
Unknown
Registered
2025-11-05
Start date
2025-11-06
Completion date
Unknown
Last updated
2025-11-11

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Dry eye disease

Interventions

Gold Standard:Hire 1 to 2 ophthalmologists with the title of deputy director or above and over 10 years of experience in dry eye diagnosis and treatment to form a team. They will jointly review all ca
Index test:The diagnostic and therapeutic recommendations generated by the large language model (LLM) and those provided by junior ophthalmologists will be compared with the expert consensus (gold sta

Sponsors

Fuzhou University Affiliated Provincial Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.Over 18 years old; 2.Patients with dry eye or related symptoms with complete clinical data were selected as the research subjects;

Exclusion criteria

Exclusion criteria: 1.Combined with other major ocular surface lesions; 2.Combined systemic diseases that affect tears; 3.Recent history of eye surgery; 4.Cases with missing key information;

Design outcomes

Primary

MeasureTime frame
Global Quality Score;

Secondary

MeasureTime frame
Safety Score of Treatment Plan;Accuracy rate of dry eye classification;The accuracy rate of treatment decisions;

Countries

China

Contacts

Public ContactLi Li

Fuzhou University Affiliated Provincial Hospital

lili_js@fjsl.com.cn+86 591 88618523

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026