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NCT07202767

Intraocular Lens Calculation Using Artificial Intelligence

Not yet recruiting Last updated 2 October 2025
What this trial tests

trial testing Swept-Source Anterior Segment OCT in Cataract in 170 participants. Not yet recruiting.

Timeline
1 November 2025
Primary endpoint
30 July 2027
30 October 2028

Quick facts

Lead sponsorJohannes Kepler University of Linz
StatusNot yet recruiting
Study typeOBSERVATIONAL
Enrollment170
Start date1 November 2025
Primary completion30 July 2027
Estimated completion30 October 2028
Sites1 location across Austria

Drugs / interventions tested

Conditions studied

Sponsor

Johannes Kepler University of Linz

Who can join

21 and older, any sex, with Cataract. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

The aim of this study is to investigate the lens diameter (LD) as a useful parameter in intraocular lens (IOL) power calculation by using several different non-invasive imaging techniques. The aim is to establish an accurate model for lens diameter estimation and subsequently evaluate the influence of the LD on the effective postoperative lens position. The comparability of the different devices in terms of variability between the biometric measurements will also be assessed. By then combining these two approaches with artificial intelligence, the aim is to develop a new approach to effectively incorporate the LD in IOL power calculation and improve patient's outcome in the long run.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other recruiting trials for Cataract

Currently open trials in the same condition.

Other Johannes Kepler University of Linz trials

Trials by the same sponsor.

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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/NCT07202767.

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