Pilot Study on Deep Learning in the Eye (IDLE)

CRG UZ Brussel

Status: Unknown

Conditions: Cataract; Central Serous Chorioretinopathy; Diabetic Retinopathy

Treatments: Other: Image classification using deep learning algorithm

Study type: Observational

Funder types: Other

Identifiers

NCT04665102

IDLE1000

Details and patient eligibility

About

Deep learning allows you to classify images using a self-learning algorithm. Transfer learning builds on an existing self-learning algorithm to enable image classification with fewer images. In this study, this technique will be applied to different image modalities in different syndromes. Retrospective study design.

Enrollment: 120 estimated patients

Sex: All

Ages: 18 to 100 years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Availability of images, which allow discrimination.

Exclusion criteria

• No availability of clear data on disease differentiation

Trial design

120 participants in 2 patient groups

No pathology

Pathology

Treatment:

Other: Image classification using deep learning algorithm