An ensemble-based approach for estimating personalized intraocular lens power

Abstract The fundamental difference between modern formulae for intraocular lens (IOL) power calculation lies on the single ad hoc regression model they use to estimate the effective lens position (ELP). The ELP is very difficult to predict and its estimation is considered critical for an accurate p...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Salissou Moutari, Jonathan E. Moore
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/e1b9b884605b4a599e90c87f44b0b52b
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:e1b9b884605b4a599e90c87f44b0b52b
record_format	dspace
spelling	oai:doaj.org-article:e1b9b884605b4a599e90c87f44b0b52b2021-11-28T12:19:58ZAn ensemble-based approach for estimating personalized intraocular lens power10.1038/s41598-021-02288-x2045-2322https://doaj.org/article/e1b9b884605b4a599e90c87f44b0b52b2021-11-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-02288-xhttps://doaj.org/toc/2045-2322Abstract The fundamental difference between modern formulae for intraocular lens (IOL) power calculation lies on the single ad hoc regression model they use to estimate the effective lens position (ELP). The ELP is very difficult to predict and its estimation is considered critical for an accurate prediction of the required IOL power of the lens to be implanted during cataract surgery. Hence, more advanced prediction techniques, which improve the prediction accuracy of the ELP, could play a decisive role in improving patient refractive outcomes. This study introduced a new approach for the calculation of personalized IOL power, which used an ensemble of regression models to devise a more accurate and robust prediction of the ELP. The concept of cross-validation was used to rigorously assess the performance of the devised formula against the most commonly used and published formulae. The results from this study show that overall, the proposed approach outperforms the most commonly used modern formulae (namely, Haigis, Holladay I, Hoffer Q and SRK/T) in terms of mean absolute prediction errors and prediction accuracy i.e., the percentage of eyes within ± 0.5D and ± 1 D ranges of prediction, for various ranges of axial lengths of the eyes. The new formula proposed in this study exhibited some promising features in terms of robustness. This enables the new formula to cope with variations in the axial length, the pre-operative anterior chamber depth and the keratometry readings of the corneal power; hence mitigating the impact of their measurement accuracy. Furthermore, the new formula performed well for both monofocal and multifocal lenses.Salissou MoutariJonathan E. MooreNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Salissou Moutari Jonathan E. Moore An ensemble-based approach for estimating personalized intraocular lens power
description	Abstract The fundamental difference between modern formulae for intraocular lens (IOL) power calculation lies on the single ad hoc regression model they use to estimate the effective lens position (ELP). The ELP is very difficult to predict and its estimation is considered critical for an accurate prediction of the required IOL power of the lens to be implanted during cataract surgery. Hence, more advanced prediction techniques, which improve the prediction accuracy of the ELP, could play a decisive role in improving patient refractive outcomes. This study introduced a new approach for the calculation of personalized IOL power, which used an ensemble of regression models to devise a more accurate and robust prediction of the ELP. The concept of cross-validation was used to rigorously assess the performance of the devised formula against the most commonly used and published formulae. The results from this study show that overall, the proposed approach outperforms the most commonly used modern formulae (namely, Haigis, Holladay I, Hoffer Q and SRK/T) in terms of mean absolute prediction errors and prediction accuracy i.e., the percentage of eyes within ± 0.5D and ± 1 D ranges of prediction, for various ranges of axial lengths of the eyes. The new formula proposed in this study exhibited some promising features in terms of robustness. This enables the new formula to cope with variations in the axial length, the pre-operative anterior chamber depth and the keratometry readings of the corneal power; hence mitigating the impact of their measurement accuracy. Furthermore, the new formula performed well for both monofocal and multifocal lenses.
format	article
author	Salissou Moutari Jonathan E. Moore
author_facet	Salissou Moutari Jonathan E. Moore
author_sort	Salissou Moutari
title	An ensemble-based approach for estimating personalized intraocular lens power
title_short	An ensemble-based approach for estimating personalized intraocular lens power
title_full	An ensemble-based approach for estimating personalized intraocular lens power
title_fullStr	An ensemble-based approach for estimating personalized intraocular lens power
title_full_unstemmed	An ensemble-based approach for estimating personalized intraocular lens power
title_sort	ensemble-based approach for estimating personalized intraocular lens power
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/e1b9b884605b4a599e90c87f44b0b52b
work_keys_str_mv	AT salissoumoutari anensemblebasedapproachforestimatingpersonalizedintraocularlenspower AT jonathanemoore anensemblebasedapproachforestimatingpersonalizedintraocularlenspower AT salissoumoutari ensemblebasedapproachforestimatingpersonalizedintraocularlenspower AT jonathanemoore ensemblebasedapproachforestimatingpersonalizedintraocularlenspower
_version_	1718408049140432896

An ensemble-based approach for estimating personalized intraocular lens power

Ejemplares similares