AI-news

For people with diabetes, a retinal photograph has traditionally answered one major question: Is diabetic retinopathy developing? However, artificial intelligence is beginning to uncover much more. Emerging retinal AI models for systemic risk assessment can detect patterns associated with cardiovascular disease, kidney disease, blood pressure, and metabolic health. As a …

Artificial intelligence is rapidly changing how healthcare professionals diagnose disease. But can computers identify kidney damage before it becomes obvious under a microscope? Researchers believe the answer may be yes. The combination of digital pathology, artificial intelligence, and diabetic kidney disease research is opening new opportunities to identify microscopic kidney …

Diabetic retinopathy remains one of the leading causes of preventable blindness worldwide. Yet despite clear screening guidelines, many patients with diabetes still miss their annual retinal exams. Busy schedules, limited specialist access, transportation barriers, and lack of awareness often delay diagnosis until vision changes become permanent. As healthcare systems search …

In 2026, diabetic retinopathy screening is entering a new era driven by artificial intelligence, tele-retinal imaging, and smarter integration into primary care workflows. Despite improved glucose monitoring and widespread use of CGM systems, diabetic retinopathy remains a leading cause of preventable blindness in adults with diabetes. So how can clinicians …

A missed diagnosis, a delayed follow-up, or a rushed primary care visit can quietly shape the course of diabetes for years. For many patients, especially those outside specialty clinics, these small gaps add up. The challenge is not a lack of clinical knowledge, but a lack of timely support where …

What happens when breakthrough treatments only reach the few who can afford or access them? That’s the growing dilemma in diabetes care. As GLP‑1 medications, digital tools, and AI reshape how we treat this chronic disease, the risk is clear: innovation could deepen inequality if we don’t act intentionally. Equity …

What if your next diabetes appointment started before you even walked in—an algorithm already having reviewed your CGM data, flagged risks, and drafted a care plan? That’s not science fiction. It’s the emerging reality of AI-powered workflows for diabetes care, where intelligent systems work behind the scenes to support clinicians …

Artificial intelligence (AI) is transforming many aspects of diabetes care, and smart insulin management powered by AI is quickly becoming one of its most promising innovations. Tools that read continuous glucose monitor (CGM) data and suggest insulin changes are rapidly entering clinical use. But while these tools are powerful, they …

AI decision support in diabetes care is reshaping how clinicians manage continuous glucose monitoring (CGM) and insulin dosing. These tools deliver quick data-driven recommendations, raising key questions: How do we preserve clinical judgment? Where does AI end and provider expertise begin? This article explains how to safely evaluate and use …

Imagine a virtual version of yourself, a “mirror you” inside a computer, where doctors and you can test different treatments, diets, or lifestyle changes — without any risk. This is not science fiction anymore. In recent years, researchers have begun applying the concept of “digital twins diabetes” — virtual patient …