Evidence map›Paper›PMID 41090992›Full record

ArticleTranslational vision science & technology2025

Predicting Intraocular Collamer Lens Vault in Myopic Patients With Shallow Anterior Chamber Using FedEYE Platform and ChatGPT.

Zhanyu Su, Zhaoxiang Wang, Shanshan Wang, Meng Ni, Jinwei Hu, Ruiwen Wang, Jie Yang, Yunxia Bai, Yonghong Xu, Shuli Di and 10 more

Abstract read
In one paragraph

Article in Translational vision science & technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

20 authors.

Zhanyu SuAier Academy of Ophthalmology, Central South University, Changsha, Hunan, China.
Zhaoxiang WangXi'an Aier Eye Hospital, Northwest University, Xi'an, Shaanxi, China.
Shanshan WangXi'an Aier Eye Hospital, Northwest University, Xi'an, Shaanxi, China.
Meng NiXi'an Aier Eye Hospital, Northwest University, Xi'an, Shaanxi, China.
Jinwei HuXi'an Aier Eye Hospital, Northwest University, Xi'an, Shaanxi, China.
Ruiwen WangXi'an Aier Eye Hospital, Northwest University, Xi'an, Shaanxi, China.
Jie YangXi'an Aier Eye Hospital, Northwest University, Xi'an, Shaanxi, China.
Yunxia BaiXi'an Aier Eye Hospital, Northwest University, Xi'an, Shaanxi, China.
Yonghong XuXi'an Aier Eye Hospital, Northwest University, Xi'an, Shaanxi, China.
Shuli DiXi'an Aier Eye Hospital, Northwest University, Xi'an, Shaanxi, China.
Yaqian XuXi'an Aier Eye Hospital, Northwest University, Xi'an, Shaanxi, China.
Zheng WangAier Academy of Ophthalmology, Central South University, Changsha, Hunan, China.
Zhuoyue ChenSchool of Medicine, Northwest University, Xi'an, Shaanxi, China.
Julio Ortega-UsobiagaDepartment of Cataract & Refractive Surgery, Clínica Baviera, Aier Eye Hospital Group, Bilbao, Spain.
Ming X WangWang Vision Institute, Aier Eye Hospital Group, Nashville, TN, USA.
Xinlong JiangInstitute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
Yiqiang ChenInstitute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
Weiwei DaiAier Academy of Ophthalmology, Central South University, Changsha, Hunan, China.
Jiansu ChenAier Academy of Ophthalmology, Central South University, Changsha, Hunan, China.
Kangjun LiAier Academy of Ophthalmology, Central South University, Changsha, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study evaluated the effectiveness of the code-free platforms FedEYE and ChatGPT in predicting vault in patients with shallow anterior chamber depth (ACD) undergoing implantable collamer lens (ICL) surgery. Methods: This retrospective study included 160 eyes with shallow ACD (<2.8 mm) and developed two code-free artificial intelligence (AI) models. An integrated neural network (INN) was developed using the FedEYE platform with ResNet and gradient-boosting trees, combined with optical coherence tomography (OCT) images and examination data, to determine how different data combinations achieve the best model performance and the correlation between parameters and vault. ChatGPT prompted with memory function and also used to validate its capability to predict vault based on these preoperative multimodal data. Results: Based on the test set results, the INN model, using the combined OCT image and examination data, achieved favorable performance with accuracy of 0.875, sensitivity of 0.857, specificity of 0.889, weighted F1 score of 0.86, and area under the curve (AUC) of 0.873. Anterior chamber angle and spherical equivalent positively correlated with vault, and age and white-to-white diameter negatively correlated. Following memory prompting, ChatGPT improved itself and reached accuracy of 0.813, recall of 0.571, weighted F1 score of 0.73, and AUC of 0.865. Conclusions: Code-free tools are particularly notable for their straightforward development and deployment. These two code-free AI models demonstrated encouraging performance in predicting vault in shallow ACD patients. Translational Relevance: Using different AI models to predict vault after ICL implantation could be of clinical significance for improving surgical safety and efficacy in shallow ACD patients.

Indexed as

Anterior ChamberLens Implantation, IntraocularMyopiaPhakic Intraocular LensesAdultArtificial IntelligenceFemaleGenerative Artificial IntelligenceHumansMaleMiddle AgedNeural Networks, ComputerRetrospective StudiesTomography, Optical CoherenceYoung Adult

Identifiers

PMID41090992
PMCPMC12533507

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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.