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A mobile app for Glaucoma diagnosis and its possible clinical applications
BACKGROUND: Nowadays, 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 patien...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7346323/ https://www.ncbi.nlm.nih.gov/pubmed/32646472 http://dx.doi.org/10.1186/s12911-020-1123-2 |
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author | Guo, Fan Li, Weiqing Zhao, Xin Qiu, Junfeng Mai, Yuxiang |
author_facet | Guo, Fan Li, Weiqing Zhao, Xin Qiu, Junfeng Mai, Yuxiang |
author_sort | Guo, Fan |
collection | PubMed |
description | BACKGROUND: Nowadays, 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. METHODS: A 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. RESULTS: For 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. CONCLUSIONS: Yanbao 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. |
format | Online Article Text |
id | pubmed-7346323 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-73463232020-07-14 A mobile app for Glaucoma diagnosis and its possible clinical applications Guo, Fan Li, Weiqing Zhao, Xin Qiu, Junfeng Mai, Yuxiang BMC Med Inform Decis Mak Research BACKGROUND: Nowadays, 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. METHODS: A 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. RESULTS: For 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. CONCLUSIONS: Yanbao 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. BioMed Central 2020-07-09 /pmc/articles/PMC7346323/ /pubmed/32646472 http://dx.doi.org/10.1186/s12911-020-1123-2 Text en © The Author(s). 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Guo, Fan Li, Weiqing Zhao, Xin Qiu, Junfeng Mai, Yuxiang A mobile app for Glaucoma diagnosis and its possible clinical applications |
title | A mobile app for Glaucoma diagnosis and its possible clinical applications |
title_full | A mobile app for Glaucoma diagnosis and its possible clinical applications |
title_fullStr | A mobile app for Glaucoma diagnosis and its possible clinical applications |
title_full_unstemmed | A mobile app for Glaucoma diagnosis and its possible clinical applications |
title_short | A mobile app for Glaucoma diagnosis and its possible clinical applications |
title_sort | mobile app for glaucoma diagnosis and its possible clinical applications |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7346323/ https://www.ncbi.nlm.nih.gov/pubmed/32646472 http://dx.doi.org/10.1186/s12911-020-1123-2 |
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