Academic Articles & Research Papers

Identifying Patients with Rapid Progression to Diabetic Retinopathy in Type 2 Diabetes: A Simple Prediction Model for Community Settings.

Prevalence and factors associated with diabetic retinopathy among diabetic patients at Arbaminch General Hospital, Ethiopia: Cross sectional study.

BackgroundCurrently 93 million people are estimated as living with diabetic retinopathy worldwide. The prevalence and risk factors of diabetic retinopathy in developed countries have been well documented; but in Ethiopia, data on prevalence...

Real-World Evaluation of AI-Driven Diabetic Retinopathy Screening in Public Health Settings: Validation and Implementation Study

Abstract BackgroundArtificial intelligence (AI) algorithms offer an effective solution to alleviate the burden of diabetic retinopathy (DR) screening in public health settings. However, there are challenges in translating diagno...

Early Retinal Microvascular Alterations in Young Type 1 Diabetic Patients without Clinical Retinopathy

The purpose of this study is to identify and quantify preclinical changes with the help of optical coherence tomography angiography (OCTA) within the retinal microcirculation of young type 1 diabetes (T1D) patients without clinical signs of...

Multi-label classification of fundus images based on graph convolutional network

Abstract Background Diabetic Retinopathy (DR) is the most common and serious microvascular complication in the diabetic population. Using computer-aided diagnosis from the fundus images has become a method of detecting retinal diseases, but...

Fundus imaging based quantum computing: Grading of severity of vision threatening diabetic retinopathy

Diabetic Retinopathy (DR) is a major complication of diabetes that can result in irreversible vision loss if not detected early. Manual ophthalmologic screening is time-consuming and subject to subjectivity, underscoring the need for accura...

Fyn Kinase: A Potential Target in Glucolipid Metabolism and Diabetes Mellitus

Fyn is widely involved in diverse cellular physiological processes, including cell growth and survival, and has been implicated in the regulation of energy metabolism and the pathogenesis of diabetes mellitus through multiple pathways. Fyn ...

Prevalence of comorbid depression and associated factors among hospitalized patients with type 2 diabetes mellitus in Hunan, China

Abstract Background Depression and diabetes are major health challenges, with heavy economic social burden, and comorbid depression in diabetes could lead to a wide range of poor health outcomes. Although many descriptive studies have highl...

Circulating and extracellular vesicle-associated non-coding RNAs in diabetic retinopathy: a stage-aware framework for network-informed biomarker panels.

Automated diabetic retinopathy grading and lesion detection based on the modified R‐FCN object‐detection algorithm

In this work, we develop a computer‐aided retinal image screening system that can perform automated diabetic retinopathy (DR) grading and DR lesion detection in retinal fundus images. We propose a modified object‐detection method for this t...

Hard exudate segmentation in retinal image with attention mechanism

Abstract Diabetic retinopathy (DR) is the main reason that causes preventable blindness. Hard exudate is one of the earliest signs of diabetic retinopathy. Precise detection of hard exudate is helpful for the early diagnosis of diabetic ret...

Deep learning applications in ophthalmology

PURPOSE OF REVIEW: To describe the emerging applications of deep learning in ophthalmology. RECENT FINDINGS: Recent studies have shown that various deep learning models are capable of detecting and diagnosing various diseases afflicting the...

Vison transformer adapter-based hyperbolic embeddings for multi-lesion segmentation in diabetic retinopathy

Abstract Diabetic Retinopathy (DR) is a major cause of blindness worldwide. Early detection and treatment are crucial to prevent vision loss, making accurate and timely diagnosis critical. Deep learning technology has shown promise in the a...

Comparing Clinical Metadata Fusion Strategies for Diabetic and Hypertensive Retinopathy Classification

Structured clinical variables may complement fundus photographs, but the most appropriate point at which to integrate them into a retinal foundation model remains uncertain. This study compares an image-only baseline with three strategies f...

Economic Evaluations of Artificial Intelligence Implementation in Diabetic Retinopathy Screening

Diabetic retinopathy (DR) is a common complication of diabetes that damages retinal blood vessels and can lead to vision impairment. The application of Artificial Intelligence (AI) in DR screening offers a promising alternative to conventio...

A review of optimization strategies for deep and machine learning in diabetic macular edema

Diabetic macular edema (DME) is a primary contributor to visual impairment in diabetic patients, necessitating precise and prompt analysis for optimal treatment. Recent breakthroughs in deep learning (DL) and machine learning (ML) have yiel...

Artificial Intelligence and Deep Learning in Ophthalmology

Artificial intelligence (AI) based on deep learning (DL) has sparked tremendous global interest in recent years. DL has been widely adopted in image recognition, speech recognition and natural language processing, but is only beginning to i...

Artificial intelligence in retina

Major advances in diagnostic technologies are offering unprecedented insight into the condition of the retina and beyond ocular disease. Digital images providing millions of morphological datasets can fast and non-invasively be analyzed in ...