Evidence map›Paper›PMID 32646472›Full record

ArticleBMC medical informatics and decision making2020

A mobile app for Glaucoma diagnosis and its possible clinical applications.

Fan Guo, Weiqing Li, Xin Zhao, Junfeng Qiu, Yuxiang Mai

Open access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 27% of its field
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

2 citing papers in PubMed, 9 citations in OpenAlex.

  1. A Novel Prediction Method for Glaucoma Detection Using Retinographies.Colombian Caribbean Conference : (C3), IEEE · 2023
    Article
  2. 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

5 authors at 1 institution in 1 country.

Fan GuoSchool of Automation, Central South University, Changsha, China. guofancsu@163.com.
Weiqing LiSchool of Automation, Central South University, Changsha, China.
Xin ZhaoSchool of Automation, Central South University, Changsha, China.
Junfeng QiuSchool of Automation, Central South University, Changsha, China.
Yuxiang MaiSchool of Automation, Central South University, Changsha, China.
Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNowadays, the latent power of technology, which can offer innovative resolutions to disease diagnosis, has awakened high-level anticipation in the community of patients as well as professionals. An easy-to-use mobile app is developed by us, which is purposefully intended for those patients with glaucoma.

methodsA mobile App has been invented for smartphones for the convenient use wherever and whenever. The corresponding experiments carried out by public retinal image database and real captured clinical data reveal the ideal classification accuracy of the App. Also, user feedback evaluation is also carried out in terms of performance test as well as and users' experience.

resultsFor clinical test using Yanbao App, we found 274 patients for the identification with 648 retinal images to be evaluated by glaucoma classification. Of the 243 glaucoma patients, 191 were screened out with an accuracy of 0.7860 (sensitivity); the number of non-glaucoma patients was 310 of 405, and the accuracy reached 0.7654 (specificity).` The total Accuracy amounted to 0.7731, and the result is close to the test performance obtained on public dataset ORIGA and DRISHTI-GS1.

conclusionsYanbao App can be applied as an innovative approach exploiting mobile technology to enhance the clinicians' efficiency and a balanced medical resources as well as a provided better tiered medical service system.

Indexed as

GlaucomaMobile ApplicationsDatabases, FactualHumansSmartphoneApp developmentClinical applicationE-healthGlaucomaMobile

Identifiers

PMID32646472
PMCPMC7346323
OpenAlexW3041120344

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.