Pilot Study on Deep Learning in the Eye

CRG UZ Brussel120 enrolled

Overview

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.

Study Type

OBSERVATIONAL

Enrollment

120

Conditions

Central Serous Chorioretinopathy Diabetic Retinopathy Cataract

Interventions

Image classification using deep learning algorithmOTHER

Image classification using deep learning algorithm

Eligibility

Sex: ALLMin age: 18 YearsMax age: 100 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: * Availability of images, which allow discrimination. Exclusion Criteria: * No availability of clear data on disease differentiation

Outcomes

Primary Outcomes

Validation of Image classification by transfer learning algorithm

Time frame: 1 year

Central Contacts

Pieter Nelis

CONTACT

+32494354198 nelispieter@gmail.com

Data from ClinicalTrials.gov

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