Pilot Study on Deep Learning in the Eye

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Brief Title

Pilot Study on Deep Learning in the Eye

Official Title

Validation of a Transfer Learning Deep Learning Algorithm for Image Classification in Multiple Pathologies

Brief Summary

      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


Primary Outcome

Validation of Image classification by transfer learning algorithm


Condition

Central Serous Chorioretinopathy

Intervention

Image classification using deep learning algorithm

Study Arms / Comparison Groups

 No pathology
Description:  

Publications

* Includes publications given by the data provider as well as publications identified by National Clinical Trials Identifier (NCT ID) in Medline.

Recruitment Information


Recruitment Status

Other

Estimated Enrollment

120

Start Date

February 1, 2021

Completion Date

December 1, 2022

Primary Completion Date

December 1, 2021

Eligibility Criteria

        Inclusion Criteria:

          -  Availability of images, which allow discrimination.

        Exclusion Criteria:

          -  No availability of clear data on disease differentiation
      

Gender

All

Ages

18 Years - 100 Years

Accepts Healthy Volunteers

Accepts Healthy Volunteers

Contacts

, +32494354198, [email protected]



Administrative Informations


NCT ID

NCT04665102

Organization ID

IDLE1000


Responsible Party

Principal Investigator

Study Sponsor

CRG UZ Brussel


Study Sponsor

, , 


Verification Date

January 2021