Predicting intraocular lens tilt using a machine learning concept.

Journal: Journal of cataract and refractive surgery

PMID: 38529959

Abstract

PURPOSE: To use a combination of partial least squares regression and a machine learning approach to predict intraocular lens (IOL) tilt using preoperative biometry data.

Authors

Klemens Waser

From the Kepler University Clinic Linz, Linz, Austria (Waser, Honeder, Hirnschall, Khalil, Pomberger, Laubichler, Mariacher, Bolz); Johannes Kepler University Linz, Linz, Austria (Waser, Honeder, Hirnschall, Khalil, Pomberger, Laubichler, Mariacher, Bolz).
Andreas Honeder
Nino Hirnschall
Haidar Khalil
Leon Pomberger
Peter Laubichler
Siegfried Mariacher
Matthias Bolz

Keywords

Aged Artificial Lens Implant Migration Biometry Female Humans Lens Implantation, Intraocular Lenses, Intraocular Machine Learning Male Middle Aged Phacoemulsification Prospective Studies Pseudophakia Refraction, Ocular Tomography, Optical Coherence Visual Acuity

External Resources

View on PubMed Access via DOI PubMed (38529959)

Predicting intraocular lens tilt using a machine learning concept.

Abstract

Authors

Keywords

External Resources

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