NCT04319055

AI-Assisted Facial Surgical Planning

Artificial Intelligence-Assisted Facial, Periocular, and Orbital Analysis and Surgical Planning

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 17,932 (actual)
• Sponsor: National Taiwan University Hospital · Academic / Other
• Sex: All
• Age: 20 Years – 65 Years
• Healthy volunteers: Not accepted

Summary

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.

Detailed description

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

• Facial Plastic and Reconstructive Surgery
• Periocular Diseases
• Orbital Diseases
• Artificial Intelligence

Timeline

• Start date: 2009-01-01
• Primary completion: 2018-12-31
• Completion: 2019-07-30
• First posted: 2020-03-24
• Last updated: 2021-02-18

Locations

1 site across 1 country: Taiwan