ArticleBiomedical engineering online2023
Predicting post-operative vault and optimal implantable collamer lens size using machine learning based on various ophthalmic device combinations.
Article in Biomedical engineering online, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Vault of the phakic intraocular lens during vertical and horizontal fixation within patient comparison.Scientific reports · 2025Trial
- Preoperative predictive factors for opaque bubble layer formation and area during small-incision lenticule extraction: predictive models based on machine learning.Eye and vision (London, England) · 2026Article
- Predicting vault after implantable collamer lens implantation using intraoperative OCT: establishment and application of models.Journal of cataract and refractive surgery · 2026Article
- Direct measurement of the horizontal and vertical ciliary sulcus placements using ultrasound biomicroscopy in myopic eyes.Journal of cataract and refractive surgery · 2026Observational
- Artificial intelligence in refractive surgery: progress, challenges, and future directions.Frontiers in cell and developmental biology · 2026Review
- Clinical Applications of Anterior Segment Optical Coherence Tomography in Managing Phakic and Secondary Intraocular Lens Implants: A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2025Review
- Using Artificial Intelligence to Predict Implantable Collamer Lens Vault: A Low Parameter-Dependent Model for Better Surgical Outcomes.Translational vision science & technology · 2025Article
- Quantitative analysis of iris-ciliary angle area to optimize ICL selection: a retrospective study.BMC ophthalmology · 2025Article
- Exploring Machine Learning Models for Vault Safety in ICL Implantation: A Comparative Analysis of Regression and Classification Models.Ophthalmology and therapy · 2025Article
- Evaluating the Predictive Accuracy of an AI-Based Tool for Postoperative Vault Estimation in Phakic Intraocular Lens Implantation.Clinical ophthalmology (Auckland, N.Z.) · 2025Article
- Prediction of postoperative vault after implantable collamer lens implantation with deep learning.International journal of ophthalmology · 2025Article
- Development and validation of a novel vault prediction formula based on structural parameters of the anterior and posterior chambers.BMC ophthalmology · 2024Observational
- Predictability comparison of sizing parameters for postoperative vault after implantable Collamer lens implantation.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2024Article
- Predicting Implantable Collamer Lens Vault Using Machine Learning Based on Various Preoperative Biometric Factors.Translational vision science & technology · 2024Article
- Comparison of the Accuracy of Seven Vault Prediction Formulae for Implantable Collamer Lens Implantation.Ophthalmology and therapy · 2024Article
- The role of anterior segment biomarkers in the development and progression of myopia.Taiwan journal of ophthalmologyReview
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
backgroundImplantable Collamer Lens (ICL) surgery has been proven to be a safe, effective, and predictable method for correcting myopia and myopic astigmatism. However, predicting the vault and ideal ICL size remains technically challenging. Despite the growing use of artificial intelligence (AI) in ophthalmology, no AI studies have provided available choices of different instruments and combinations for further vault and size predictions. This study aimed to fill this gap and predict post-operative vault and appropriate ICL size utilizing the comparison of numerous AI algorithms, stacking ensemble learning, and data from various ophthalmic devices and combinations.
resultsThis retrospective and cross-sectional study included 1941 eyes of 1941 patients from Zhongshan Ophthalmic Center. For both vault prediction and ICL size selection, the combination containing Pentacam, Sirius, and UBM demonstrated the best results in test sets [R
conclusionsStrategies based on multiple machine learning algorithms for different ophthalmic devices and combinations are applicable for vault predicting and ICL sizing, potentially improving the safety of the ICL implantation. Moreover, our findings emphasize the crucial role of UBM in the perioperative period of ICL surgery, as it provides key STS measurements that outperformed WTW measurements in predicting post-operative vault and optimal ICL size, highlighting its potential to enhance ICL implantation safety and accuracy.
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Registered trials
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.