Accuracy of Low-Cost, Smartphone-Based Retinal Photography for Diabetic Retinopathy Screening: A Systematic Review

Prayogo, Mohammad Eko; Zaharo, Alfia Fatma; Damayanti, Novandriati Nur Rizky; Widyaputri, Felicia; Thobari, Jarir At; Susanti, Vina Yanti; Sasongko, Muhammad Bayu

doi:10.2147/opth.s416422

Cited by 4 publications

(1 citation statement)

References 44 publications

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“…Новые данные свидетельствуют, что чувствительность доступных недорогих устройств на базе смартфонов для скрининга ДР является приемлемой, а их специфичность, особенно при обнаружении ДР и макулярного диабетиче-ского отека, оказывалась значительной. Эти данные подтверждают потенциальные возможности использования смартфонов для скрининга на ДР в условиях ограниченных ресурсов [29].…”

Section: использование смартфонов для скрининга на диабетическую рети...unclassified

Telemedicine Screening for Diabetic Retinopathy Using Digital Technology: Foreign Experience

Andreev,

Kamynina

2024

City Healthcare

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Background. Timely detection and treatment of diabetic retinopathy (DR) could prevent the development of blindness. However, large number of patients are diagnosed at late stages when effective treatment becomes impossible. In this context, active screening for DR plays an important role. Various screening programs have been developed, including programs using digital technologies.Objective. To analyze and summarize the literature data on digitalization of DR screening.Materials and methods. The study was carried out based on the results of a search in the PubMed / Medline bibliographic database and the Google system. The used keywords were “diabetes”, “retinopathy”, “telemedi-cine”, “digital technologies”, “artificial intelligence” and others. Relevant publications were selected by exam-ining the titles and abstracts of articles.Results. The study addressed the approaches to organizing the telemedicine programs of DR screening. The examples of innovative digital technologies for performing diagnostic studies as well as the characteristics of various electronic systems and devices are presented. It was noted that the DR screening could be performed in a local center with data transfer to a regional specialized diagnostic (analytical) center where telemedicine analysis is done. All diagnostic information is available to the diabetologist who prescribes and adjusts ther-apy. This operating principle facilitates the interaction between various specialists and thus increases the efficiency of screening.Discussion. Although the telemedicine screening for diabetic retinopathy has already been introduced in a number of countries, it is still at its early stages of development. Many modern technologies such as portable mobile devices could be adapted and used in the implementation of telemedicine programs. Deep machine learning algorithms and other artificial intelligence-based approaches demonstrate excellent results. Some systems have already received regulatory approval. Conclusions. The early diagnostics of diabetic retinopathy could be improved by integrating innovative screening technologies in a unified digital platform implemented in routine clinical practice.

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Section: использование смартфонов для скрининга на диабетическую рети...unclassified

Telemedicine Screening for Diabetic Retinopathy Using Digital Technology: Foreign Experience

Andreev,

Kamynina

2024

City Healthcare

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Artificial intelligence and machine learning for anaphylaxis algorithms

Miller,

Manious,

Portnoy

2024

Current Opinion in Allergy &Amp; Clinical Immunology

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Purpose of review Anaphylaxis is a severe, potentially life-threatening allergic reaction that requires rapid identification and intervention. Current management includes early recognition, prompt administration of epinephrine, and immediate medical attention. However, challenges remain in accurate diagnosis, timely treatment, and personalized care. This article reviews the integration of artificial intelligence and machine learning in enhancing anaphylaxis management. Recent findings Artificial intelligence and machine learning can analyze vast datasets to identify patterns and predict anaphylactic episodes, improve diagnostic accuracy through image and biomarker analysis, and personalize treatment plans. Artificial intelligence-powered wearable devices and decision support systems can facilitate real-time monitoring and early intervention. The ethical considerations of artificial intelligence use, including data privacy, transparency, and bias mitigation, are also discussed. Summary Future directions include the development of predictive models, enhanced diagnostic tools, and artificial intelligence-driven educational resources. By leveraging artificial intelligence and machine learning, healthcare providers can improve the management of anaphylaxis, ensuring better patient outcomes and advancing personalized medicine.

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Diabetic macular edema (DME): dissecting pathogenesis, prognostication, diagnostic modalities along with current and futuristic therapeutic insights

Sakini,

Hamid,

Alkhuzaie

et al. 2024

Int J Retin Vitr

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One of the most common health concerns disturbing people within working years globally is diabetes mellitus (DM). One well-known consequence of DM is vascular damage, which can manifest as macro- and microangiopathy affecting the ocular retina. Therefore, Diabetic macular edema (DME) is a major sight-threatening complication of diabetic retinopathy (DR) worldwide. It is the most prevalent cause of significant vision impairment in diabetic patients. Long-term vision loss can be avoided by following early DME treatment guidelines in everyday life. Hence, there are various therapeutic approaches for DME management. Currently, the first-line treatment for DME is anti-VEGF family drugs, such as ranibizumab, brolucizumab, bevacizumab, and aflibercept. Nevertheless, relapses of the disease, inadequate response, and resistance during anti-VEGF therapy are still seen because of the intricate pathophysiological foundation of the disease. Consequently, there is an excellent requirement for therapeutic approaches to advance and become better at controlling diseases more satisfactorily and require fewer treatments overall. We conducted a thorough literature search in the current review to present a comprehensive overview of the primary data about the current DME therapeutic agents. We also covered the novel advances in DME management and probable future treatments being investigated and developed. This review recommended that Large clinical trials should afford sufficient evidence to support these innovative treatment modalities.

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Accuracy of Low-Cost, Smartphone-Based Retinal Photography for Diabetic Retinopathy Screening: A Systematic Review

Cited by 4 publications

References 44 publications

Telemedicine Screening for Diabetic Retinopathy Using Digital Technology: Foreign Experience

Telemedicine Screening for Diabetic Retinopathy Using Digital Technology: Foreign Experience

Artificial intelligence and machine learning for anaphylaxis algorithms

Diabetic macular edema (DME): dissecting pathogenesis, prognostication, diagnostic modalities along with current and futuristic therapeutic insights

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