Retinal Vein Occlusion–Background Knowledge and Foreground Knowledge Prospects—A Review

Journal of Clinical Medicine, Journal Year: 2024, Volume and Issue: 13(13), P. 3950 - 3950

Published: July 5, 2024

Thrombosis of retinal veins is one the most common vascular diseases that may lead to blindness. The latest epidemiological data leave no illusions burden on healthcare system, as impacted by patients with this diagnosis, will increase worldwide. This obliges scientists search for new therapeutic and diagnostic options. In 21st century, there has been tremendous progress in imaging techniques, which facilitated a better understanding mechanisms related development vein occlusion (RVO) its complications, consequently enabled introduction treatment methods. Moreover, artificial intelligence (AI) likely assist selecting best option near future. aim comprehensive review re-evaluate old but still relevant RVO confront them studies. paper provide detailed overview current treatment, prevention, future possibilities regarding RVO, well clarifying mechanism macular edema disease entity.

Language: Английский

---

Analysis and comparison of retinal vascular parameters under different glucose metabolic status based on deep learning

International Journal of Ophthalmology, Journal Year: 2024, Volume and Issue: 17(9), P. 1581 - 1591

Published: Aug. 20, 2024

To develop a deep learning-based model for automatic retinal vascular segmentation, analyzing and comparing parameters under diverse glucose metabolic status (normal, prediabetes, diabetes) to assess the potential of artificial intelligence (AI) in image segmentation predicting prediabetes diabetes.

Language: Английский

---

Enhancing Ophthalmic Diagnosis and Treatment with Artificial Intelligence

Medicina, Journal Year: 2025, Volume and Issue: 61(3), P. 433 - 433

Published: Feb. 28, 2025

The integration of artificial intelligence (AI) in ophthalmology is transforming the field, offering new opportunities to enhance diagnostic accuracy, personalize treatment plans, and improve service delivery. This review provides a comprehensive overview current applications future potential AI ophthalmology. algorithms, particularly those utilizing machine learning (ML) deep (DL), have demonstrated remarkable success diagnosing conditions such as diabetic retinopathy (DR), age-related macular degeneration, glaucoma with precision comparable to, or exceeding, human experts. Furthermore, being utilized develop personalized plans by analyzing large datasets predict individual responses therapies, thus optimizing patient outcomes reducing healthcare costs. In surgical applications, AI-driven tools are enhancing procedures like cataract surgery, contributing better recovery times reduced complications. Additionally, AI-powered teleophthalmology services expanding access eye care underserved remote areas, addressing global disparities availability. Despite these advancements, challenges remain, concerning data privacy, security, algorithmic bias. Ensuring robust governance ethical practices crucial for continued conclusion, research should focus on developing sophisticated models capable handling multimodal data, including genetic information histories, provide deeper insights into disease mechanisms responses. Also, collaborative efforts among governments, non-governmental organizations (NGOs), technology companies essential deploy solutions effectively, especially low-resource settings.

Language: Английский

---

Enhancing ophthalmology students’ awareness of retinitis pigmentosa: assessing the efficacy of ChatGPT in AI-assisted teaching of rare diseases—a quasi-experimental study

Frontiers in Medicine, Journal Year: 2025, Volume and Issue: 12

Published: March 18, 2025

Retinitis pigmentosa (RP) is a rare retinal dystrophy often underrepresented in ophthalmology education. Despite advancements diagnostics and treatments like gene therapy, RP knowledge gaps persist. This study assesses the efficacy of AI-assisted teaching using ChatGPT compared to traditional methods educating students about RP. A quasi-experimental was conducted with 142 medical randomly assigned control (traditional review materials) groups. Both groups attended lecture on completed pre- post-tests. Statistical analyses learning outcomes, times, response accuracy. significantly improved post-test scores (p < 0.001), but group required less time (24.29 ± 12.62 vs. 42.54 20.43 min, p 0.0001). The also performed better complex questions regarding advanced treatments, demonstrating AI's potential deliver accurate current information efficiently. enhances efficiency comprehension diseases hybrid educational model combining AI can address gaps, offering promising approach for modern

Language: Английский

---

Multi-resolution visual Mamba with multi-directional selective mechanism for retinal disease detection

Frontiers in Cell and Developmental Biology, Journal Year: 2024, Volume and Issue: 12

Published: Oct. 11, 2024

Introduction Retinal diseases significantly impact patients’ quality of life and increase social medical costs. Optical coherence tomography (OCT) offers high-resolution imaging for precise detection monitoring these conditions. While deep learning techniques have been employed to extract features from OCT images classification, convolutional neural networks (CNNs) often fail capture global context due their focus on local receptive fields. Transformer-based methods, the other hand, suffer quadratic complexity when handling long-range dependencies. Methods To overcome limitations, we introduce Multi-Resolution Visual Mamba (MRVM) model, which addresses dependencies with linear computational image classification. The MRVM model initially employs convolution subsequently utilizes retinal By integrating multi-scale features, enhances classification accuracy overall performance. Additionally, multi-directional selection mechanism (MSM) within improves feature extraction by concentrating various directions, thereby better capturing complex, orientation-specific patterns. Results Experimental results demonstrate that excels in differentiating lesions, achieving superior compared traditional accuracies 98.98\% 96.21\% two public datasets, respectively. Discussion This approach a novel perspective accurately identifying could contribute development more robust artificial intelligence algorithms recognition systems image-assisted diagnosis.

Language: Английский

---

Association of Retinal Veinocclusion with Homocysteine and Antithrombin III in Middle-Aged Adults

Advances in Clinical Medicine, Journal Year: 2024, Volume and Issue: 14(05), P. 940 - 949

Published: Jan. 1, 2024

Language: Английский

---