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30% of patients with diabetes develop disease-related complications. AI-based assistants offer personalized recommendations to improve habits.
Diabetes stands as a critical global health issue, accelerating the risk of widespread complications, such as cardiovascular diseases, nerve damage (neuropathy), kidney disease (nephropathy), and eye damage (retinopathy). These issues contribute significantly to the morbidity and mortality among the diabetic population, with about 30% of individuals with diabetes experiencing such complications. The prevalence and impact of diabetes complications are subject to variation, influenced by demographic factors and individual patient risk profiles, thereby complicating consistent treatment approaches [1].
AI-based prediction models can assess the risk of multiple diabetic complications with high precision. These models utilize multidimensional datasets to provide valuable tools for healthcare professionals, particularly in preventive care settings. This allows for early intervention and personalized treatment plans to mitigate the risk of complications [2]
The assistant's predictive capabilities are based on guidelines established in the “Abbreviated Standards of Diabetes Care: 2023 for Primary Care Providers” (4). Use these guidelines to provide personalized advice aimed at improving the patient's lifestyle choices and reducing the risk of complications.
Diabetes stands as a critical global health issue, accelerating the risk of widespread complications, such as cardiovascular diseases, nerve damage (neuropathy), kidney disease (nephropathy), and eye damage (retinopathy). These issues contribute significantly to the morbidity and mortality among the diabetic population, with about 30% of individuals with diabetes experiencing such complications. The prevalence and impact of diabetes complications are subject to variation, influenced by demographic factors and individual patient risk profiles, thereby complicating consistent treatment approaches [1].
AI-based prediction models can assess the risk of multiple diabetic complications with high precision. These models utilize multidimensional datasets to provide valuable tools for healthcare professionals, particularly in preventive care settings. This allows for early intervention and personalized treatment plans to mitigate the risk of complications [2]
The ADA placed the cost of diagnosed diabetes in 2017 at $327.2 billion. Undiagnosed diabetes (7.9%, $31.7 billion), prediabetes (10.7%, $43.4 billion), and GDM (0.4%, $1.6 billion) combine with the prior estimate for diagnosed diabetes to total $403.9 billion annually [3].
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The assistant's predictive capabilities are based on guidelines established in the “Abbreviated Standards of Diabetes Care: 2023 for Primary Care Providers” (4). Use these guidelines to provide personalized advice aimed at improving the patient's lifestyle choices and reducing the risk of complications.
