AI-Assisted Facial Surgical Planning

Status Completed

Clinical Trial 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.

Clinical Trial 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. ;

Study Design

Related Conditions & MeSH terms

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

Clinical Trial Details

NCT number	NCT04319055
Study type	Observational
Source	National Taiwan University Hospital
Contact
Status	Completed
Phase
Start date	January 1, 2009
Completion date	July 30, 2019

View Details

See also
Status	Clinical Trial	Phase
Completed	`NCT04589078` - Polyp REcognition Assisted by a Device Interactive Characterization Tool - The PREDICT Study
Completed	`NCT03857438` - Correlation of Audiovisual Features With Clinical Variables and Neurocognitive Functions in Bipolar Disorder, Mania
Completed	`NCT04735055` - Artificial Intelligence Prediction for the Severity of Acute Pancreatitis
Not yet recruiting	`NCT05452993` - Screening for Diabetic Retinopathy in Pharmacies With Artificial Intelligence Enhanced Retinophotography	N/A
Not yet recruiting	`NCT04337229` - Evaluation of Comfort Behavior Levels of Newborns With Artificial Intelligence Techniques	N/A
Completed	`NCT05687318` - A Clinical Trial of the Effectiveness and Safety of Software Assisting Diagnose the Intestinal Polyp Digestive Endoscopy by Analysis of Colonoscopy Medical Images From Electronic Digestive Endoscopy Equipment	N/A
Recruiting	`NCT06051682` - Optimization of the Diagnosis of Bone Fractures in Patients Treated in the Emergency Department by Using Artificial Intelligence for Reading Radiological Images in Comparison With Traditional Reading by the Emergency Doctor.	N/A
Not yet recruiting	`NCT06039917` - Effect of the Automatic Surveillance System on Surveillance Rate of Patients With Gastric Premalignant Lesions	N/A
Not yet recruiting	`NCT06362629` - AI App for Management of Atopic Dermatitis	N/A
Recruiting	`NCT06164002` - A I in the Prediction of Clinical Performance, Marginal Fit and Fracture Resistance of Vertical Versus Horizontal Margin Designs Fabricated With 2 Ceramic Materials	N/A
Recruiting	`NCT06059378` - Real-life Implementation of an AI-based Optical Diagnosis	N/A
Completed	`NCT05517889` - Repeatability and Stability of Healthy Skin Features on OCT
Completed	`NCT04816981` - AI-EBUS-Elastography for LN Staging	N/A
Completed	`NCT05006092` - Surveillance Modified by Artificial Intelligence in Endoscopy (SMARTIE)	N/A
Recruiting	`NCT04535466` - Diagnosis Predictive Modle for Dense Density Breast Tissue Based on Radiomics
Enrolling by invitation	`NCT04719117` - Retrograde Cholangiopancreatography AI Assisted System Validation on Effectiveness and Safety
Completed	`NCT04399590` - Comparing the Number of False Activations Between Two Artificial Intelligence CADe Systems: the NOISE Study
Recruiting	`NCT04126265` - Artificial Intelligence-assisted Colonoscopy for Detection of Colon Polyps	N/A
Recruiting	`NCT06255808` - Development of Assist Tool for Breast Examination Using the Principle of Ultrasonic Sensor
Recruiting	`NCT04131530` - Automatic Evaluation of Inflammation Activity in Ulcerative Colitis Using pCLE With Artificial Intelligence