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NCT04665102: IDLE

Pilot Study on Deep Learning in the Eye

Status unknown Last updated 7 January 2021
What this trial tests

trial testing Image classification using deep learning algorithm in Central Serous Chorioretinopathy in 120 participants. Status unknown.

Timeline
1 February 2021
Primary endpoint
1 December 2021
1 December 2022

Quick facts

Lead sponsorCRG UZ Brussel
StatusStatus unknown
Study typeOBSERVATIONAL
Enrollment120
Start date1 February 2021
Primary completion1 December 2021
Estimated completion1 December 2022

Drugs / interventions tested

Conditions studied

Sponsor

CRG UZ Brussel — full company profile →

Who can join

Adults 18 to 100, any sex, with Central Serous Chorioretinopathy or Diabetic Retinopathy. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

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.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other recruiting trials for Central Serous Chorioretinopathy

Currently open trials in the same condition.

Other CRG UZ Brussel trials

Trials by the same sponsor.

Verify against primary sources

Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT04665102.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing