Diabetes Mellitus is a severe, chronic disease that occurs when blood glucose levels rise
above certain limits. Over the last years, machine and deep learning techniques have been …

Abstract Machine learning (ML) is a rapidly advancing field with increasing utility in health
care. We conducted a systematic review and critical appraisal of ML applications in vascular …

Medical costs are one of the most common recurring expenses in a person's life. Based on
different research studies, BMI, ageing, smoking, and other factors are all related to greater …

Aim To construct predictive models of diabetes complications (DCs) by big data machine
learning, based on electronic medical records. Methods Six groups of DCs were considered …

Importance Systems-level barriers to diabetes care could be improved with population
health planning tools that accurately discriminate between high-and low-risk groups to guide …

The advancement of deep learning and artificial intelligence has resulted in the
development of state-of-the-art language models, such as ChatGPT. This technology can …

Monitoring diabetes saves lives. To this end, we introduce a novel, unobtrusive, and readily
deployable in-ear device for the continuous and non-invasive measurement of blood …

Background Micro-and macrovascular complications are a major burden for individuals with
diabetes and can already arise in a prediabetic state. To allocate effective treatments and to …

One hundred years have passed since the discovery of insulin—an achievement that
transformed diabetes from a fatal illness into a manageable chronic condition. The decades …

Background: Hypoglycemia is a common adverse event in the treatment of diabetes. To
efficiently cope with hypoglycemia, effective hypoglycemia prediction models need to be …