Relevance. Diabetic retinopathy (DR) is one of the serious complications of diabetes mellitus (DM). If diagnosed untimely and treated inadequately, DR can lead to vision loss due to complications such as hemophthalmos and retinal detachment. Purpose of the study. The aim of this study was to explore the evolution of automated diagnosis of diabetic retinopathy from visualization and automatic segmentation of the ocular fundus imaging to the diagnosis of stages of diabetic retinopathy by deep learning algorithms in artificial intelligence programs. Materials and methods. In this study we conducted a search on PubMed, ScienceDirect, and similar search engines for studies published from 2006 to 2023 using a combination of keywords in the medical field (ophthalmology, diabetic retinopathy, screening) and in the field of machine learning (artificial intelligence, deep learning, neural connectivity). We identified 160 articles and incorporated them into the analysis. The paper is organized as follows: we sequentially analyzed different computer programs as they became more complex. Results and conclusion. Artificial intelligence programs, rapidly developing in recent years, are successfully used to diagnose vision-threatening diabetic retinopathy. Artificial intelligence programs have demonstrated sensitivity ranging from 82–99.1% and specificity ranging from 63–90% in detecting vision-threateningdiabetic retinopathy. Artificial intelligence programs will undoubtedly help doctors timely diagnose vision-threatening diabetic retinopathy. AI-enabled screening programs will help reach hard-to-reach, densely populated, low-income areas. The authors hope that similar programs that use artificial intelligence to diagnose diabetic retinopathy will become widely available throughout the world.
| Mualliflar | Ф. А. Бахритдинова, Guzal Kangilbaeva, Ф. М. Урманова, И. Ф. Набиева, А. З. Журабекова |
|---|---|
| Jurnal | Передовая Офтальмология |
| Nashr sanasi | 2024-06-19 |
| Jild | 8 |
| Son | 2 |
| Betlar | 11-18 |
| Til | ru |
| DOI | 10.57231/j.ao.2024.8.2.002 |
DOI: 10.57231/j.ao.2024.8.2.002 · Maqolaning asl sahifasi
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