Evidence map›Paper›PMID 38456011›Full record

ReviewFrontiers in bioengineering and biotechnology2024

Progress in clinical research and applications of retinal vessel quantification technology based on fundus imaging.

Naimei Chen, Zhentao Zhu, Weihua Yang, Qiang Wang

Abstract readReview
In one paragraph

Review in Frontiers in bioengineering and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
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  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. RBAD: A Dataset and Benchmark for Retinal Vessels Branching Angle Detection.... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics · 2024
    Article
  11. Article
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

4 authors.

Naimei ChenDepartment of Ophthalmology, Huaian Hospital of Huaian City, Huaian, China.
Zhentao ZhuDepartment of Ophthalmology, Huaian Hospital of Huaian City, Huaian, China.
Weihua YangDepartment of Ophthalmology, Shenzhen Eye Hospital, Jinan University, Shenzhen, China.
Qiang WangDepartment of Ophthalmology, Third Affiliated Hospital, Wenzhou Medical University, Ruian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Retinal blood vessels are the only directly observed blood vessels in the body; changes in them can help effective assess the occurrence and development of ocular and systemic diseases. The specificity and efficiency of retinal vessel quantification technology has improved with the advancement of retinal imaging technologies and artificial intelligence (AI) algorithms; it has garnered attention in clinical research and applications for the diagnosis and treatment of common eye and related systemic diseases. A few articles have reviewed this topic; however, a summary of recent research progress in the field is still needed. This article aimed to provide a comprehensive review of the research and applications of retinal vessel quantification technology in ocular and systemic diseases, which could update clinicians and researchers on the recent progress in this field.

Indexed as

artificial intelligenceocular diseasesretinal vasculatureretinal vessel quantificationsystemic diseases

Identifiers

PMID38456011
PMCPMC10917897

What OpenQuestion holds

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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.