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Diabetes

Chronic Diseases

Nutrition

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Artificial intelligence

Global Solutions & Projects

NEW FRONTIERS OF DIGITAL MEDICINE

Artificial intelligence for the prevention, diagnosis, and treatment of diabetes.

AI is now a strategic ally for doctors and researchers, opening new perspectives in the prevention, diagnosis, and management of chronic diseases. Meteda integrates AI solutions particularly focused on diabetic retinopathy and severe diabetes-related complications.

Only one third of people with diabetes undergo annual eye examinations, despite diabetic retinopathy being a serious and frequent complication that can lead to irreversible vision loss.

Retinopathy Screening with AI Algorithms

Meteda acquired Portuguese company Retmarker SA, developer of the AI algorithm Screening DR, already used on over 500,000 patients and validated by numerous international scientific publications. Now enhanced with deep learning techniques, the algorithm supports physicians in early detection of diabetic retinopathy, enabling timely interventions and reducing the risk of irreversible vision loss.

    Demonstrated high clinical sensitivity and specificity. Automated analysis of retinal images, delivering fast and accurate results. Clinical decision-support for screening purposes; not intended to serve as a medico-legal diagnostic report.

Predictive Algorithms for Diabetes Complications

AI-based screening and predictive algorithms are valuable tools supporting diabetologists: they help personalize care pathways, avoid therapeutic inertia, and optimize patient management. Beyond clinical value, AI contributes to more sustainable healthcare resource management, reducing costs related to preventable diseases and improving scheduling of visits and access.

Leveraging extensive expertise in clinical data management and MetaClinic® integration, Meteda has developed and validated AI algorithms capable of accurately estimating the risk of serious complications in people with diabetes. These tools, already adopted in many Italian diabetes centers, analyze large volumes of clinical data within seconds, assign a risk level (low, moderate, high, very high), and support clinicians in therapeutic decision-making.
Their clinical use has been shown to improve metabolic control, encourage adoption of innovative therapies, and overcome clinical inertia, promoting more personalized and effective diabetes management.