Predicting post-operative vault and optimal implantable collamer lens size using machine learning based on various ophthalmic device combinations
Abstract
BACKGROUND: Implantable 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.
RESULTS: This 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 [R2 = 0.499 (95% CI 0.470-0.528), mean absolute error = 130.655 (95% CI 128.949-132.111), accuracy = 0.895 (95% CI 0.883-0.907), AUC = 0.928 (95% CI 0.916-0.941)]. Sulcus-to-sulcus (STS), a parameter from UBM, ranked among the top five significant contributors to both post-operative vault and optimal ICL size prediction, consistently outperforming white-to-white (WTW). Moreover, dual-device combinations or single-device parameters could also effectively predict vault and ideal ICL size, and excellent ICL selection prediction was achievable using…
Read the paper
Related studies
- Combining in silico and in vitro approaches to identification of potent inhibitor against phospholipase A2 (PLA2)
- In silico and in vitro studies: investigating the chemical composition, DFT, molecular docking, and dynamic simulation of Satureja candidissima (Munby) Briq essential oil as a potential antibacterial agent
- Quercetin combined with ciprofloxacin and gentamicin inhibits biofilm formation and virulence in Staphylococcus aureus
- In silico study of the mechanism of action, pharmacokinetic and toxicological properties of some N-methylanthranilates and their analogs
- Anticonvulsant Effects of Citronellal, Daidzin, and Phytol, Possibly Through GABAA Receptor and Voltage-Gated Sodium Channel Interaction Pathways: In Vivo and In Silico Studies
- 2-Phenylcyclopropylmethylamine (PCPMA) Derivatives as D3R-Selective Ligands for 3D-QSAR, Docking and Molecular Dynamics Simulation Studies
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.