Development of AI Model for Uveitis Progression and Prognosis

NCT ID: NCT04705103

Last Updated: 2021-01-12

Study Results

Results pending

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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Recruitment Status

UNKNOWN

Total Enrollment

450 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-01-10

Study Completion Date

2022-12-30

Brief Summary

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Uveitis is a recurrent inflammation of the eye that can lead to vision loss with various and complicated etiologies. There are many difficulties in uveitis management due to the requirement of long-term monitoring and treatment. This study intends to establish a longitudinal cohort of uveitis patients to colloect multimodal clinical data including visual acuity, intraocular pressure, anterior segment photography, fundus photography, fluoroscopy and other ophthalmic examinations, and final diagnosis in order to use artificial intelligence and deep learning technology to extract ocular features, explore the association with the progression and prognosis of uveitis and finally establish a disease management model for uveitis.

Detailed Description

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Conditions

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Uveitis

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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initial

No interventions assigned to this group

relapse

No interventions assigned to this group

inactive

No interventions assigned to this group

Eligibility Criteria

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Inclusion Criteria

* Participants who were diagnosed as uveitis, including the initial stage or relapse, or remission of uveitis.

Exclusion Criteria

* Participants who cannnot cooperate with ocualr examination.
Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Sun Yat-sen University

OTHER

Sponsor Role lead

Responsible Party

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Haotian Lin

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Central Contacts

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Haotian Lin, M.D.,Ph.D

Role: CONTACT

13802793086

shuyi Zhang, M.D.

Role: CONTACT

15622177115

Other Identifiers

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2020KYPJ185

Identifier Type: -

Identifier Source: org_study_id

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