Madhav Kohli, Pallavi Pandey, Vikash Jakhmola, Supriyo Saha, Meenu Chaudhary, Arif Nur Muhammad Ansori, Arvind Negi
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引用次数: 0
Abstract
Millions of people worldwide have diabetes, a disease that is becoming more common and has substantial socioeconomic costs. Artificial intelligence (AI) improves diabetes management, diagnosis, and prevention. AI-powered tools enable early detection of diabetes and its complications, including diabetic retinopathy, using sophisticated algorithms and large-scale data analysis. Wearable devices and continuous glucose monitors, integrated with AI, facilitate personalized treatment plans and real-time insights, improving glycemic control and overall health outcomes. Advanced machine learning models demonstrate high accuracy in diagnosing and predicting diabetes, while automated insulin delivery systems and bolus calculators enhance insulin management, reducing risks of hypo- and hyperglycemia. Despite these advancements, challenges such as cost, accessibility, device interoperability, and ethical considerations persist. The development of new digital biomarkers, individualized clinical metrics, and patient-centric solutions is critical for optimizing care. While AI holds immense promise in alleviating the global diabetes burden, addressing these limitations through sustained innovation and collaboration is essential. This review underscores the transformative potential of AI in revolutionizing diabetes care, enabling advancement for enhanced prevention, precise diagnosis, and effective management strategies.
Supplementary information: The online version contains supplementary material available at 10.1007/s40200-025-01648-y.
期刊介绍:
Journal of Diabetes & Metabolic Disorders is a peer reviewed journal which publishes original clinical and translational articles and reviews in the field of endocrinology and provides a forum of debate of the highest quality on these issues. Topics of interest include, but are not limited to, diabetes, lipid disorders, metabolic disorders, osteoporosis, interdisciplinary practices in endocrinology, cardiovascular and metabolic risk, aging research, obesity, traditional medicine, pychosomatic research, behavioral medicine, ethics and evidence-based practices.As of Jan 2018 the journal is published by Springer as a hybrid journal with no article processing charges. All articles published before 2018 are available free of charge on springerlink.Unofficial 2017 2-year Impact Factor: 1.816.