Evidence map›Paper›PMID 39322767›Full record

ArticleEye (London, England)2024

Accuracy assessment of artificial intelligence IOL calculation formulae: utilizing the heteroscedastic statistics and the Eyetemis Analysis Tool.

Olga Reitblat, Noa Heifetz, Kathryn Durnford, Jeff H Pettey, Randall J Olson, Eitan Livny, Ashlie A Bernhisel, Irit Bahar, Ruti Sella

Abstract read
In one paragraph

Article in Eye (London, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Olga ReitblatDepartment of Ophthalmology, Rabin Medical Center, Petach Tikva, Israel.ORCID 0000-0002-8417-4440
Noa HeifetzFaculty of Medicine, Tel Aviv University, Tel Aviv, Israel.ORCID 0009-0000-6790-3819
Kathryn DurnfordUniversity of Utah School of Medicine, Salt Lake City, UT, USA.
Jeff H PetteyDepartment of Ophthalmology and Visual Sciences, John A. Moran Eye Center, University of Utah, Salt Lake City, UT, USA.ORCID 0000-0003-4587-8768
Randall J OlsonDepartment of Ophthalmology and Visual Sciences, John A. Moran Eye Center, University of Utah, Salt Lake City, UT, USA.
Eitan LivnyDepartment of Ophthalmology, Rabin Medical Center, Petach Tikva, Israel.
Ashlie A BernhiselDepartment of Ophthalmology and Visual Sciences, John A. Moran Eye Center, University of Utah, Salt Lake City, UT, USA.
Irit BaharDepartment of Ophthalmology, Rabin Medical Center, Petach Tikva, Israel.ORCID 0000-0003-2008-0717
Ruti SellaDepartment of Ophthalmology, Rabin Medical Center, Petach Tikva, Israel. SellaSvetlit.Ruti@mayo.edu.ORCID 0000-0002-4748-4685

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo analyse the accuracy of artificial intelligence (AI)-driven intraocular (IOL) calculation formulae, together with established formulae using the heteroscedastic methodology and the Eyetemis Analysis Tool.

methodsData from 404 eyes who underwent uneventful phacoemulsification with implantation of the SN60WF IOL were retrospectively reviewed. IOL power calculations were performed using the Barrett Universal II (BUII), EVO 2.0, Hoffer QST, K6, Ladas Super Formula (LSF), Nallasamy, PEARL-DGS and RBF 3.0 formulae. The SD of the prediction error (PE), served as the primary metric for accuracy. The mean absolute deviation (MAD) and the predictability rates within intervals from ±0.25 D to ±1.50 D were also evaluated. The Eyetemis Analysis Tool was used for further validation.

resultsThe SD ranged from 0.468 (Nallasamy) to 0.510 (LSF). The Nallasamy formula had a significantly lower SD than the BUII (0.505, p = 0.025) and K6 (0.489, p = 0.022) formulae. The Nallasamy formula also exhibited the lowest MAD (0.358) with a significant difference compared with the Hoffer QST formula (0.384, p < 0.001). Finally, a significantly higher percentage of eyes achieving ± 0.50 D of the target refraction was seen using the Nallasamy formula (77.19%) compared with the Hoffer QST (71.04%, p = 0.019) and Ladas Super Formula (70.79%, p = 0.030) formulae.

conclusionsThe Nallasamy formula, incorporating AI technology, demonstrated superior accuracy according to the analysis guidelines for PE statistics for non-gaussian datasets recommended by Holladay et al. and the online Eyetemis Analysis Tool.

Indexed as

Artificial IntelligenceBiometryLenses, IntraocularLens Implantation, IntraocularOptics and PhotonicsPhacoemulsificationRefraction, OcularAgedAged, 80 and overFemaleHumansMaleMiddle AgedPseudophakiaReproducibility of ResultsRetrospective Studies

Identifiers

PMID39322767
PMCPMC11621322

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.