Evidence map›Paper›PMID 38495723›Full record

ArticleBiomedical optics express2024

Controllable editing via diffusion inversion on ultra-widefield fluorescein angiography for the comprehensive analysis of diabetic retinopathy.

Xiao Ma, Zexuan Ji, Qiang Chen, Lexin Ge, Xiaoling Wang, Changzheng Chen, Wen Fan

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomedical optics express, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Xiao MaSchool of Computer Science and Engineering, Nanjing University of Science and Technology, 200 XiaoLinwei, Nanjing, Jiangsu 210094, China.ORCID https://orcid.org/0000-0002-1842-5029
Zexuan JiSchool of Computer Science and Engineering, Nanjing University of Science and Technology, 200 XiaoLinwei, Nanjing, Jiangsu 210094, China.ORCID https://orcid.org/0000-0003-1665-0270
Qiang ChenSchool of Computer Science and Engineering, Nanjing University of Science and Technology, 200 XiaoLinwei, Nanjing, Jiangsu 210094, China.ORCID https://orcid.org/0000-0002-6685-2447
Lexin GeDepartment of Ophthalmology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu 210029, China.
Xiaoling WangEye Center, Renmin Hospital of Wuhan University, No. 9 ZhangZhiDong Street, Wuchang District, Wuhan, Hubei 430060, China.
Changzheng ChenEye Center, Renmin Hospital of Wuhan University, No. 9 ZhangZhiDong Street, Wuchang District, Wuhan, Hubei 430060, China.
Wen FanDepartment of Ophthalmology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu 210029, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

By incorporating multiple indicators that facilitate clinical decision making and effective management of diabetic retinopathy (DR), a comprehensive understanding of the progression of the disease can be achieved. However, the diversity of DR complications poses challenges to the automatic analysis of various information within images. This study aims to establish a deep learning system designed to examine various metrics linked to DR in ultra-widefield fluorescein angiography (UWFA) images. We have developed a unified model based on image generation that transforms input images into corresponding disease-free versions. By incorporating an image-level supervised training process, the model significantly reduces the need for extensive manual involvement in clinical applications. Furthermore, compared to other comparative methods, the quality of our generated images is significantly superior.

Identifiers

PMID38495723
PMCPMC10942674

What OpenQuestion holds

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Read underepoch 390

Registered trials

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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.