Clinical trials: Ocular Images
Ophthalmology, Artificial Intelligence
Screening and Identifying Hepatobiliary Diseases Via Deep Learning Using Ocular Images
Artificial Intelligence may provide insight into exploring the potential covert association behind and reveal some early ocular architecture changes in individuals with hepatobiliary disorders.
- Conditions
- Ophthalmology, Artificial Intelligence, Hepatobiliary Disease
- Trial name
- NCT04213183
- Testing
- Hepatobiliary Disorders
- Where
- China
- Volunteers
- 1,789 people, healthy volunteers welcome
- Sponsor
- Sun Yat-sen University
Keratoconus, Eye Diseases
Development of a Keratoconus Detection Algorithm by Deep Learning Analysis and Its Validation on Eyestar Images
Monocentric clinical study to develop an imaging analysis algorithm for the Eyestar 900 to identify keratoconus corneas and improve biometry for intraocular lens calculations
- Conditions
- Keratoconus, Eye Diseases, Cataract, Corneal Ectasia
- Trial name
- DKDA (NCT04763785)
- Testing
- Corneal tomography with Eyestar 900, Corneal tomography with Pentacam, Biometry with IOL-Master
- Where
- Switzerland
- Volunteers
- 4,800 people, healthy volunteers welcome
- Sponsor
- Insel Gruppe AG, University Hospital Bern
Retinal Diseases, Artificial Intelligence
Artificial Intelligence System for Assessing Image Quality of Fundus Images and Its Effects on Diagnosis
Fundus images are widely used in ophthalmology for the detection of diabetic retinopathy, glaucoma and other diseases. In real-world practice, the quality of fundus images can be unacceptable, which can undermine diagnostic…
- Trial name
- NCT04289064
- Testing
- Taking a fundus image
- Where
- China
- Volunteers
- 300 people, healthy volunteers welcome
- Sponsor
- Sun Yat-sen University
Covid19
Eye Detection to Identify Novel Coronavirus Infection
The eye characteristics of patients with COVID-19 and those without the disease were analyzed, and whether they had the disease or not was judged according to the eye characteristics.
- Trial name
- NCT04907981
- Testing
- Novel coronavirus infection
- Where
- China
- Volunteers
- 232 people, healthy volunteers welcome
- Sponsor
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Trachoma
Smartphone App for Taking Images of Conjunctivae
Trachomatous inflammation-follicular (TF) is diagnosed by looking for clinical signs of infection of everted eyelids (conjunctivae) of children.
- Trial name
- NCT03997487
- Testing
- TOFTEE
- Where
- Tanzania
- Volunteers
- 125 people, healthy volunteers welcome
- Sponsor
- London School of Hygiene and Tropical Medicine
Ophthalmological Disorder
Development and Validation of a Deep Learning System for Multiple Ocular Fundus Diseases Using Retinal Images
Retinal images can reflect both fundus and systemic conditions (diabetes and cardiovascular disease) and firstly to be used for medical artificial intelligence (AI) algorithm training due to its advantages of clinical…
- Trial name
- NCT04213430
- Testing
- diagnostic
- Where
- China
- Volunteers
- 300,000 people, healthy volunteers welcome
- Sponsor
- Sun Yat-sen University
Jaundice, Deep Learning
A Prospective Study: Smart Phone Application for Measure Serum Bilirubin Through Sclera Images
The primary efficacy endpoints are the standard deviation and coefficient of determination (R2) between predicted and actual values for the bilirubin regression model, and the grading accuracy for the jaundice severity…
- Conditions
- Jaundice, Deep Learning, Hyperbilirubinemia, Sclera
- Trial name
- NCT06421844
- Where
- China
- Volunteers
- 270 people, healthy volunteers welcome
- Sponsor
- Air Force Military Medical University, China