Principal Component Analysis of a Real-World Cohort of Descemet Stripping Automated Endothelial Keratoplasty and Descemet Membrane Endothelial Keratoplasty Cases: Demonstration of a Powerful Data-Mining Technique for Identifying Areas of Research.
Fiche publication
Date publication
mai 2024
Journal
Cornea
Auteurs
Membres identifiés du Cancéropôle Est :
Dr GOETZ Christophe
Tous les auteurs :
Perone JM, Goetz C, Zevering Y, Derumigny A
Lien Pubmed
Résumé
Principal component analysis (PCA) is a descriptive exploratory statistical technique that is widely used in complex fields for data mining. However, it is rarely used in ophthalmology. We explored its research potential with a large series of eyes that underwent 3 keratoplasty techniques: Descemet membrane endothelial keratoplasty (DMEK), conventional Descemet stripping automated endothelial keratoplasty (ConDSAEK), or ultrathin-DSAEK (UT-DSAEK).
Référence
Cornea. 2024 05 29;: