School of Automation, Central South University, Changsha, China.
BMC Med Inform Decis Mak. 2020 Jul 9;20(Suppl 3):128. doi: 10.1186/s12911-020-1123-2.
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.
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.
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.
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.
如今,技术的潜在力量可以为疾病诊断提供创新的解决方案,这在患者和专业人士群体中引起了高度期待。我们开发了一款易于使用的移动应用程序,专门针对青光眼患者。
我们为智能手机发明了一款移动应用程序,以便随时随地方便使用。通过公共视网膜图像数据库和实际采集的临床数据进行的相应实验,揭示了该应用程序理想的分类准确性。此外,还对性能测试和用户体验进行了用户反馈评估。
在使用 Yanbao App 进行临床测试时,我们发现 274 名患者的 648 张视网膜图像用于青光眼分类评估。在 243 名青光眼患者中,有 191 名被准确筛查出来,准确率为 0.7860(敏感性);非青光眼患者的数量为 405 名中的 310 名,准确率达到 0.7654(特异性)。总体准确率达到 0.7731,结果与公共数据集 ORIGA 和 DRISHTI-GS1 的测试性能相近。
Yanbao App 可以作为一种利用移动技术的创新方法,提高临床医生的工作效率和平衡医疗资源,并提供更好的分级医疗服务体系。