Evidence map›Paper›PMID 41776035›Full record

ArticleNature biomedical engineering2026

An ophthalmic video foundation model for surgical recognition and navigation with wet-lab porcine eye validation.

Puxun Tu, Ce Zheng, Xiaoling Xie, Jiao Lv, Meng Xie, Jinming Guo, Shengjie Yin, Kunliang Qiu, Yue Wei, Chongyang Wang and 12 more

Abstract read
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In one paragraph

Article in Nature biomedical engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Puxun Tu *Institute of Biomedical Manufacturing and Life Quality Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China.ORCID http://orcid.org/0000-0003-4809-9081
Ce Zheng *Department of Ophthalmology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China. zhengce@xinhuamed.com.cn.ORCID http://orcid.org/0000-0001-7146-9138
Xiaoling Xie *Joint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong, Shantou University Medical College, Shantou, China.ORCID http://orcid.org/0009-0002-3255-0341
Jiao LvDepartment of Ophthalmology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Meng XieDepartment of Ophthalmology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jinming GuoJoint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong, Shantou University Medical College, Shantou, China.
Shengjie YinJoint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong, Shantou University Medical College, Shantou, China.
Kunliang QiuJoint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong, Shantou University Medical College, Shantou, China.
Yue WeiShanghai Mediworks Precision Instruments Co. Ltd, Shanghai, China.
Chongyang WangShanghai Mediworks Precision Instruments Co. Ltd, Shanghai, China.
Jingfeng CaiShanghai Aier Eye Hospital, Shanghai, China.
Wei MiDepartment of Ophthalmology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yafu WangDepartment of Ophthalmology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xiao ZhangJiaozuo Apex Eye Hospital, Jiaozuo, China.
Danba JiachuKham Eye Centre, Kandze Prefecture People's Hospital, Kangding, China.
Kun PengTaizhou Aier Eye Hospital, Taizhou, China.
Wanqi ZhangGuangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China.
Fengfeng TongHuzhou Aier Eye Hospital, Huzhou, China.
Huiying ChuHuzhou Aier Eye Hospital, Huzhou, China.
Peiquan ZhaoDepartment of Ophthalmology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China. zhaopeiquan@xinhuamed.com.cn.ORCID http://orcid.org/0000-0002-5092-9550
Mingzhi ZhangJoint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong, Shantou University Medical College, Shantou, China. zmz@jsiec.org.ORCID http://orcid.org/0000-0001-9032-7274
Xiaojun ChenInstitute of Biomedical Manufacturing and Life Quality Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China. xiaojunchen@sjtu.edu.cn.ORCID http://orcid.org/0000-0002-0298-4491

Funding

China Postdoctoral Science Foundation 2025M772924National Natural Science Foundation of China (National Science Foundation of China) 82330063National Natural Science Foundation of China (National Science Foundation of China) 823B2045National Natural Science Foundation of China (National Science Foundation of China) 82571270
6 · The paper itself

Abstract

Foundation models in artificial intelligence are revolutionizing healthcare by utilizing large-scale unlabelled data for pretraining. However, their intraoperative applications remain underexplored owing to limited surgical data and the challenges of real-time deployment. Here we show the development of the ophthalmic video foundation model (OVFM), designed for microscopic ophthalmic surgical recognition and navigation. Leveraging a self-supervised video transformer structure and trained on an ophthalmic video dataset comprising 1.1 million clips across 144 surgical types, OVFM learns the spatiotemporal motion features of ophthalmic procedures. We demonstrate OVFM's superior performance across seven downstream tasks. To enable real-time use, we applied knowledge distillation, reducing the model's size while retaining its accuracy, which allows for deployment on surgical microscope units. In cataract surgeries performed by ten surgeons on wet-lab porcine eyes, the OVFM-powered system enhanced surgical performance and reduced skill gaps, demonstrating notable potential for real-time, intraoperative applications across various surgical fields.

Identifiers

PMID41776035

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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.