Research on Precision Diagnosis and Treatment Decision of Common Eye Diseases Based on Artificial Intelligence
NCT ID: NCT07078552
Last Updated: 2025-07-22
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
368 participants
OBSERVATIONAL
2024-01-01
2025-05-01
Brief Summary
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Can video-based eyelid measurements and levator muscle function grading provide useful guidance for the treatment of congenital ptosis in children?
Participants are children diagnosed with congenital ptosis. Their blinking behavior will be recorded using a smartphone, and eyelid morphology and muscle strength will be assessed from the video data.
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Detailed Description
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The second module focuses on levator function grading. The automated grading results were compared against clinical assessments by senior oculoplastic specialists, which served as the gold standard, to evaluate the model's accuracy. Additionally, we compared the model's performance to that of junior ophthalmology residents to assess the system's clinical assistive value in real-world scenarios.
Based on these modules, we developed a smartphone-based application for remote ptosis assessment. A multi-center clinical validation study was designed to evaluate the feasibility, consistency, and generalizability of the system in different clinical settings.
Conditions
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Study Design
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CASE_CONTROL
CROSS_SECTIONAL
Study Groups
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congenital ptosis
ptosis
no intervention
Interventions
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ptosis
no intervention
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
18 Years
ALL
Yes
Sponsors
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Shanghai Jiao Tong University School of Medicine
OTHER
Tianjin Eye Hospital
OTHER
Second Affiliated Hospital, School of Medicine, Zhejiang University
OTHER
Responsible Party
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Locations
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2 nd Affiliated Hospital, School of Medicine, Zhejiang University, China
Hangzhou, Zhejiang, China
Countries
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Other Identifiers
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2023-1035
Identifier Type: -
Identifier Source: org_study_id
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