Preconditioning of clinical data for intraocular lens formula constant optimisation using Random Forest Quantile Regression Trees

Preconditioning of clinical data for intraocular lens formula constant optimisation using Random Forest Quantile Regression Trees

Purpose: To implement a fully data driven strategy for identifying outliers in clinical datasets used for formula constant optimisation, in order to achieve proper formula predicted refraction after cataract surgery, and to assess the capabilities of this outlier detection method. Methods: 2 clinica...

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Bibliographic Details
Main Authors: Achim Langenbucher, Nóra Szentmáry, Alan Cayless, Jascha Wendelstein, Peter Hoffmann
Format: Article
Language:English
Published: Elsevier 2024-11-01
Series:Zeitschrift für Medizinische Physik
Subjects:
Outlier detection
Quantile regression tree
Random forest regression
Formula prediction error
Constant optimisation
Lens power calculation
Online Access:http://www.sciencedirect.com/science/article/pii/S0939388922001295
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