SynthesisInternational ophthalmology2024
Comparing the accuracy of intraocular lens power calculation formulas using artificial intelligence and traditional formulas in highly myopic patients: a meta-analysis.
Synthesis in International ophthalmology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- Outcomes on pseudophakic mini-monovision with monofocal intraocular lens on intermediate vision with immediate sequential bilateral cataract surgery.Eye (London, England) · 2026Article
- [Calculating IOL power - principles, development and current challenges].Die Ophthalmologie · 2026Review
- Evaluating predictive accuracy of intraocular lens power calculation formulas in high axial myopia: A comparative analysis.Indian journal of ophthalmology · 2026Article
- Distance Visual Outcomes of Trifocal Intraocular Lenses in Highly Myopic Eyes Without Myopic Maculopathy.Clinical ophthalmology (Auckland, N.Z.) · 2026Article
- Improved IOL Power Calculation With Femtosecond Laser Enhanced Refractive Outcome Prediction.Translational vision science & technology · 2025Article
- Global trends and hotspots in artificial intelligence for high myopia: a bibliometric analysis.Frontiers in medicine · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
purposeThe accuracy of intraocular lens (IOL) calculations is one of the key indicators for determining the success of cataract surgery. However, in highly myopic patients, the calculation errors are relatively larger than those in general patients. With the continuous development of artificial intelligence (AI) technology, there has also been a constant emergence of AI-related calculation formulas. The purpose of this investigation was to evaluate the accuracy of AI calculation formulas in calculating the power of IOL for highly myopic patients.
methodsWe searched the relevant literature through August 2023 using three databases: PubMed, EMBASE, and the Cochrane Library. Six IOL calculation formulas were compared: Kane, Hill-RBF, EVO, Barrett II, Haigis, and SRK/T. The included metrics were the mean absolute error (MAE) and percentage of errors within ± 0.25 D, ± 0.50 D, and ± 1.00 D.
resultsThe results showed that the MAE of Kane was significantly lower than that of Barrett II (mean difference = - 0.03 D, P = 0.02), SRK/T (MD = - 0.08 D, P = 0.02), and Haigis (MD = - 0.12 D, P < 0.00001). The percentage refractive prediction errors for Kane at ± 0.25 D, ± 0.50 D, and ± 1.00 D were significantly greater than those for SRK/T (P = 0.007, 0.003, and 0.01, respectively) and Haigis (P = 0.009, 0.0001, and 0.001, respectively). No statistically significant differences were noted between Hill-RBF and Barret, but Hill-RBF was significantly better than SRK/T and Haigis.
conclusionThe AI calculation formulas showed more accurate results compared with traditional formulas. Among them, Kane has the best performance in calculating IOL degrees for highly myopic patients.
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Registered trials
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