For the achievement of the Horizon Europe project results, PRAESIIDIUM, numerous research groups are combining their expertise to develop innovative strategies for the prevention of type 2 diabetes, integrating mathematical models, biological simulations, and reliable, explainable artificial intelligence tools.
The special feature of this issue is once again dedicated to the stories of three experts involved in the European project PRAESIIDIUM: Alessia Paglialonga, Laura Azzimonti, and Paolo Tieri.
Special Issue 3 is dedicated to presenting — and discussing — reliable, interpretable, and generalizable models, which are essential in the medical field.
Why is prevention, even before prediabetes appears, important?
36% of European adults live with undiagnosed diabetes, which can cause potentially life-threatening complications if not treated promptly and adequately.
541 million adults have “blood glucose levels higher than normal but not high enough to be classified as diabetes” (IDF Diabetes Atlas, 10th edition).
“Impaired fasting glucose” is an intermediate condition also known as prediabetes, as it can precede the onset of type 2 diabetes.
The most important point is that prediabetes is reversible if diagnosed early and properly, through lifestyle interventions such as a healthy diet and regular physical activity (WHO 2014 and IDF recommendations).
STEP FuturAbility District is a dynamic, interactive experiential journey that allows students to immerse themselves in today’s ongoing digital revolution. For schools, we offer the
The autumn program in the regional Hubs of the Dicolab. Digital Culture project is packed with opportunities for those who want to learn about the
The courses of the Dicolab. Digital Culture program, promoted by the Ministry of Culture and funded by the PNRR Cultura 4.0, will resume in September
How do clinicians and researchers address the growing need to integrate Artificial Intelligence (AI) and machine learning tools into the management of type 2 diabetes? How does clinical practice change when
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