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Diabetes Complications Prediction: AI Solutions for Better Patient Outcomes

30% of patients with diabetes develop disease-related complications. AI-based assistants offer personalized recommendations to improve habits.

Problem

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 (3). 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)(2).

The magnitude of this challenge is further illustrated by the sheer number of those affected—roughly 422 million people globally have diabetes, according to the World Health Organization (1). Furthermore, diabetes caused an estimated 1.6 million deaths directly in 2016 (2). The economic implications are equally staggering, with global costs related to diabetes reaching approximately $1.3 trillion in 2015 (3). This data highlights the significant personal and economic toll of diabetes and the imperative to develop proactive prevention and management strategies to mitigate these consequences.

Why it matters

  • Diabetes is a critical global health issue, causing complications like cardiovascular diseases, neuropathy, nephropathy, and retinopathy in about 30% of patients.
  • With 422 million people affected worldwide and approximately 1.6 million diabetes-related deaths in 2016, the impact of diabetes is profound.
  • The global economic cost of diabetes reached $1.3 trillion in 2015, highlighting the urgent need for effective prevention and management strategies.

Solution

"DiaManage AI" is a digital health assistant created to assist endocrinologists in diabetes management, providing up-to-date guidelines and personalized management strategies to early address risk factors and warning signs of complications, promoting timely medical actions.

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Datasources

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.

Citations

  1. M. Zeng et al., "Deep learning for diabetic kidney disease: a systematic review," MDPI Applied Sciences, vol. 11, no. 5, p. 3030, 2021.
  2. R. Y. Gianchandani et al., "Predicting diabetes complications: An AI approach," Nature Digital Medicine, vol. 4, no. 1, p. 29, 2021.
  3. J. Pillay et al., "Artificial intelligence in prediction of secondary cardiovascular disease in patients with diabetes: a meta-analysis," Journal of the American Heart Association, vol. 10, no. 5, e017999, 2021.
  4. Diabetes Care Standards: 2023 Abbreviated for Primary Care Providers, Clinical Diabetes, vol. 41, no. 1, pp. 4–31, 2022.

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