ARTIFICIAL INTELLIGENCE IN PREDICTING CLINICAL AND LABORATORY DYNAMICS IN POST-COVID-19 PATIENTS WITH DIABETES MELLITUS
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Artificial Intelligence (AI) is transforming medical diagnostics and treatment planning by enabling in-depth data analysis and prediction modeling. This study explores the application of AI in assessing the clinical and laboratory parameters of patients with diabetes mellitus (DM) in the post-COVID period, focusing on early detection and prevention of complications. Machine learning (ML) algorithms, including regression analysis and neural networks, were applied to parameters like blood glucose, HbA1c, insulin, C-peptide, and inflammatory markers. The AI-based tool, “Post-COVID Type 2 Diabetes Prediction and Management” (DGU41902), showed promising results, achieving certification and demonstrating seamless integration with existing medical information systems. Our findings suggest that AI can support early intervention strategies, ultimately improving patient outcomes.
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