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Clinical Study on the Effect of Domestic Large AI Models in Health Education for Patients with Dry Eye

Preliminary Evaluation of Response Quality and Clinical Feasibility of Intelligent Health Education for Dry Eye Patients Based on a Domestic Large Language Model

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600128021
Enrollment
Unknown
Registered
2026-07-13
Start date
2026-07-15
Completion date
Unknown
Last updated
2026-07-20

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

Conditions

Dry eye

Interventions

LLM-1 group:Large Language Model (LLM)-1
LLM-2 group:Large Language Model (LLM)-2

Sponsors

Tianjin Medical University Eye Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Age = 18 years; 2. Clearly diagnosed with dry eye according to the "China Expert Consensus on Clinical Diagnosis and Treatment of Dry Eye (2024)"; 3. Conscious; 4. Able to read and understand Chinese; 5. Willing to participate and sign the informed consent form.

Exclusion criteria

Exclusion criteria: 1.Consolidate cognitive impairments, mental illnesses and other conditions that may affect comprehension or communication abilities; 2.Unable to cooperate in completing the questionnaire test;

Design outcomes

Primary

MeasureTime frame
Consistency between AI cross-review and expert manual evaluation;Response quality, including accuracy, completeness, standardization, clinical guidance, and clarity.;Patients' understanding, satisfaction, and trust in content generated by LLMs;—

Countries

China

Contacts

Public ContactQi Yuanyuan

Tianjin Medical University Eye Hospital

qy890110@sina.com+86 22 8642 8866

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Jul 23, 2026