AI-Assisted Facial Surgical Planning

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

COMPLETED

Total Enrollment

17932 participants

Study Classification

OBSERVATIONAL

Study Start Date

2009-01-01

Study Completion Date

2019-07-30

Brief Summary

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Computer vision using deep learning architecture is broadly used in auto-recognition. In the research, the deep learning model which is trained by categorized single-eye images is applied to achieve the good performance of the model in blepharoptosis auto-diagnosis.

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Detailed Description

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This auto-diagnosis system of blepharoptosis using machine learning architecture will assist in telemedicine, such as early screening of childhood ptosis for prompt referral and treatment. People could use this software via mobile devices to get a primitive diagnosis before they reach the physicians. Furthermore, in primary health care, where there is no oculoplastic surgeon, the software could assist primary care physicians or general ophthalmologists, in identifying the need for a referral.

Conditions

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Facial Plastic and Reconstructive Surgery Periocular Diseases Orbital Diseases Artificial Intelligence

Study Design

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Observational Model Type

CASE_ONLY

Study Time Perspective

RETROSPECTIVE

Eligibility Criteria

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Inclusion Criteria

1. The participants who were 20-year-old or above,
2. Surgical informed consent was endorsed by the participants themselves,
3. Participants who have surgical indications of the oculofacial surgeries, and
4. The participants who agreed on photograph taking after explanation by the surgeon at outpatient clinics.

Exclusion Criteria

1. The participants who were 19-year-old or under,
2. The participants who don't have surgical indications of the oculofacial surgeries,
3. The participants who were designed for minimal invasive treatments, such as Botox or any kind of fillers injection,
4. The participants who refused photograph taking for any reason, and
5. The participants who are not available for standard quality of photograph taking, such as bedridden patients.

Minimum Eligible Age

20 Years

Maximum Eligible Age

65 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No