Evidence map›Paper›PMID 42337008›Full record

ArticleNPJ digital medicine2026

IVCM-Insight: automated interactive interpretation of in vivo confocal microscopy.

Zijun Zhang, Shangyang Jiang, Zhiqun Wang, Yang Zhang, Kexin Chen, Mingda Wei, Qingquan Shi, Yuan Wei, Jinding Pang, Xinxin Lu and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in NPJ digital medicine, 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

11 authors.

Zijun Zhang *Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing, China.
Shangyang Jiang *Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing, China.
Zhiqun WangBeijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing, China.
Yang ZhangBeijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing, China.
Kexin ChenBeijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing, China.
Mingda WeiBeijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing, China.
Qingquan ShiBeijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing, China.
Yuan WeiBeijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing, China.
Jinding PangBeijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing, China.
Xinxin LuBeijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing, China.
Qingfeng LiangBeijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing, China. liangqingfeng@ccmu.edu.cn.

Funding

Beijing Natural Science Foundation L254095
6 · The paper itself

Abstract

In vivo confocal microscopy (IVCM) is a critical ophthalmic examination that provides in vivo cytological and neurological information essential for diagnosing corneal and certain systemic diseases, but its clinical utility is limited by time-consuming interpretation and the need for subspecialty expertise. We developed IVCM-Insight, an artificial intelligence (AI) system integrating image-text contrastive learning with large language models (LLMs) for automated report generation and interactive question answering (QA). Based on 30,368 IVCM images and 4155 paired clinical reports, the model was trained with contrastive alignment, image-conditioned language modeling, and multi-image consistency loss to produce structured diagnostic reports while a domain-adapted LLM supported patient-centered QA. Automated evaluation showed strong agreement with the reference reports: Bilingual Evaluation Understudy (BLEU)-1 to BLEU-4 scores were 0.69, 0.58, 0.47, and 0.41, Recall-Oriented Understudy for Gisting Evaluation (ROUGE-L) was 0.67, Consensus-based Image Description Evaluation (CIDEr) was 1.85, and Metric for Evaluation of Translation with Explicit Ordering (METEOR) was 0.66. In addition, the multi-label classification achieved an accuracy of 0.96 and an F1 score of 0.80. Manual assessment by corneal specialists rated report accuracy (4.17), completeness (4.19), coherence (4.70), and diagnostic support (4.06), with excellent inter-rater reliability; QA outputs achieved high accuracy (4.33), relevance (4.54), and non-harmfulness (4.81). Representative cases, including cytomegalovirus, fungal, and Acanthamoeba keratitis, demonstrated accurate detection of key findings and clinically safe explanations. To our knowledge, IVCM-Insight is the first dedicated AI system for comprehensive IVCM interpretation, with potential to enhance diagnostic efficiency, strengthen physician-patient communication, and broaden access to advanced corneal imaging across care settings.

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.