EVO-ICL Vault Prediction: A Data Wrangling Framework Integrating Multicenter Big Data and Machine Learning

Xiaoli Li; Hongbin Lin; Guo‐Liang Fan; Zonghui Yan; Wentian Zhou; Feng Zhu; Xiaoqin Su; Yi Liu; Ling Ling; Yongjin Li; Chao Liao; Zhen Qiu; Mingkui Tan; Quan Liu

doi:10.1007/s40123-025-01288-8

Abstract

The development of DVIS is valuable for ICL vault prediction models, as it provides a data wrangling strategy that improves ML efficiency. Experimental results confirm the applicability of this synergistic method in enhancing existing ML approaches for ICL vault prediction, thereby facilitating more informed clinical decision-making in ICL implantation surgery.

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Year: 2025
Type: article
Citations: 0
Access: Closed

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APA Style

                            
                                    Xiaoli Li, 
                                
                                    Hongbin Lin, 
                                
                                    Guo‐Liang Fan
                                
                                et al.
                            
                            (2025). 
                            EVO-ICL Vault Prediction: A Data Wrangling Framework Integrating Multicenter Big Data and Machine Learning. 
                            Ophthalmology and Therapy
                            
                            .
                            https://doi.org/10.1007/s40123-025-01288-8

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DOI: 10.1007/s40123-025-01288-8