This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...

Quadrant-specific changes in superficial vascular complex vessel density, particularly in the 16- to 21-mm temporal region, are potential early biomarkers for diabetic retinopathy. Widefield ...

Tear fluid is emerging as an attractive source of diagnostic information because it can be collected easily and non-invasively. Changes in tear composition often reflect underlying physiological ...

In research published in the journal Gut, investigators from the University of Alabama at Birmingham report that restoring tryptophan metabolism in the gut microbiome can prevent or reverse diabetic ...

Diabetic retinopathy (DR), a leading cause of vision impairment among working-age adults, affects approximately 146 million individuals globally, with projections estimating an increase to 180 million ...

Sticking to your medication plan, managing your blood sugar, and taking care of your mental health can all be important components of self-care for diabetic retinopathy. Self‑care can’t cure diabetic ...

As technology advances in diabetes care with continuous glucose monitors, insulin pumps and AI-driven alerts, another kind of intelligence is proving just as powerful: a dog’s nose. Across the country ...

Ensemble deep-learning system with xAI (Grad-CAM) for automated diabetic retinopathy detection and staging using retinal fundus images.

Diabetic retinopathy (DR), the leading cause of blindness globally, is currently detected via the ETDRS diabetic retinopathy severity scale (DRSS). While effective, there are now new ways to screen, ...

Hypoglycemia is linked to an increased risk for and progression of diabetic retinopathy, according to new research presented at The Retina Society (TRS) Annual Meeting 2025. Severe hypoglycemia is ...