Artificial intelligence for diabetes complications: Detection, prediction, and clinical management

Abstract

The rapid advancement of artificial intelligence (AI) technology has the potential to optimize the detection, prediction, and management of diabetes and its complications. This review explores the latest developments in the research and innovation of AI-driven applications for the management of both chronic and acute diabetes complications. In terms of chronic complications, this review focuses on microvascular complications, including diabetic retinopathy, kidney disease, and neuropathy, as well as macrovascular complications such as cardiovascular disease. For acute complications, the emphasis is on critical conditions, including severe hypoglycemic events and diabetic ketoacidosis. AI algorithms, particularly deep learning algorithms, have demonstrated remarkable promise in the early detection and prediction of diabetes complications through the effective analysis of multimodal data, including medical images, electronic health records, continuous glucose monitoring, etc. This review underscores the potential of AI in the intelligent management of diabetes complications, while highlighting its assistive role for healthcare professionals in improving diagnostic effectiveness and guiding comprehensive diabetes care.

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