AIMC Topic: Diabetic Retinopathy

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A multi model deep net with an explainable AI based framework for diabetic retinopathy segmentation and classification.

Scientific reports
Diabetic Retinopathy (DR) is a serious condition affecting diabetes people caused by hemorrhage in the light-sensitive retinal area. DR sufferers should receive urgent therapy to avoid vision loss. The intelligent medical diagnosis system for DR is e...

D-GET: Group-Enhanced Transformer for Diabetic Retinopathy Severity Classification in Fundus Fluorescein Angiography.

Journal of medical systems
Early detection of Diabetic Retinopathy (DR) is vital for preserving vision and preventing deterioration of eyesight. Fundus Fluorescein Angiography (FFA), recognized as the gold standard for diagnosing DR, effectively reveals abnormalities in retina...

Investigation and validation of genes associated with endoplasmic reticulum stress in diabetic retinopathy using various machine learning algorithms.

Experimental eye research
BACKGROUND: Diabetic retinopathy (DR) is a common complication of diabetes, with Endoplasmic reticulum stress (ERS) playing a key role in cellular adaptation, injury, or apoptosis, impacting disease pathology. This study aimed to identify early diagn...

Performance of a Deep Learning Diabetic Retinopathy Algorithm in India.

JAMA network open
IMPORTANCE: While prospective studies have investigated the accuracy of artificial intelligence (AI) for detection of diabetic retinopathy (DR) and diabetic macular edema (DME), to date, little published data exist on the clinical performance of thes...

Enhancing Ophthalmic Diagnosis and Treatment with Artificial Intelligence.

Medicina (Kaunas, Lithuania)
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 ove...

MSTNet: Multi-scale spatial-aware transformer with multi-instance learning for diabetic retinopathy classification.

Medical image analysis
Diabetic retinopathy (DR), the leading cause of vision loss among diabetic adults worldwide, underscores the importance of early detection and timely treatment using fundus images to prevent vision loss. However, existing deep learning methods strugg...

Development and validation of predictive models for diabetic retinopathy using machine learning.

PloS one
OBJECTIVE: This study aimed to develop and compare machine learning models for predicting diabetic retinopathy (DR) using clinical and biochemical data, specifically logistic regression, random forest, XGBoost, and neural networks.

Diagnostic Accuracy of IDX-DR for Detecting Diabetic Retinopathy: A Systematic Review and Meta-Analysis.

American journal of ophthalmology
PURPOSE: Diabetic retinopathy (DR) is a leading cause of vision loss worldwide, making early detection critical to prevent blindness. IDX-DR, an FDA-approved autonomous artificial intelligence (AI) system, has emerged as an innovative solution to imp...