Evidence map›Paper›PMID 40500350›Full record

ReviewNPJ digital medicine2025

Embodied artificial intelligence in ophthalmology.

Yao Qiu, Xiaolan Chen, Xinyuan Wu, Yunqian Li, Pusheng Xu, Kai Jin, Xianwen Shang, Peranut Chotcomwongse, Mingguang He, Danli Shi

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Article
  6. Review
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

10 authors.

Yao Qiu *School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
Xiaolan Chen *School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
Xinyuan Wu *School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
Yunqian LiState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China.
Pusheng XuSchool of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
Kai JinEye Center, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Xianwen ShangSchool of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
Peranut ChotcomwongseVitreoretina Unit, Department of Ophthalmology, Rajavithi Hospital, Rungsit University, Bangkok, Thailand.
Mingguang HeSchool of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong. mingguang.he@polyu.edu.hk.
Danli ShiSchool of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong. danli.shi@polyu.edu.hk.

Funding

the Global STEM Professorship Scheme P0046113the Start-up Fund for RAPs under the Strategic Hiring Scheme from HKSAR P0048623
6 · The paper itself

Abstract

Embodied artificial intelligence (EAI) integrates perception, memory, reasoning and action through physical interaction, enabling multimodal dynamic learning and real-time feedback. In ophthalmology, EAI supports data-driven decision-making, improving the precision and personalization of diagnosis, surgery, and treatment. It also holds transformative potential in medical education and scientific research by simulating clinical scenarios and accelerating discovery. This perspective highlights EAI's unique potential while addressing current challenges in data, interpretation, and ethics, and outlines future directions for its clinical integration.

Identifiers

PMID40500350
PMCPMC12159142

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.