English
Related papers

Related papers: Toward Short-Term Glucose Prediction Solely Based …

200 papers

The rising rates of diabetes necessitate innovative methods for its management. Continuous glucose monitors (CGM) are small medical devices that measure blood glucose levels at regular intervals providing insights into daily patterns of…

Quantitative Methods · Quantitative Biology 2024-10-10 Renat Sergazinov , Elizabeth Chun , Valeriya Rogovchenko , Nathaniel Fernandes , Nicholas Kasman , Irina Gaynanova

With continuous glucose monitoring (CGM), data-driven models on blood glucose prediction have been shown to be effective in related work. However, such (CGM) systems are not always available, e.g., for a patient at home. In this work, we…

Computers and Society · Computer Science 2024-04-10 Tu Nguyen , Markus Rokicki

Understanding how biomarker distributions evolve over time is a central challenge in digital health and chronic disease monitoring. In diabetes, changes in the distribution of glucose measurements can reveal patterns of disease progression…

Machine Learning · Statistics 2026-03-26 Antonio Álvarez-López , Marcos Matabuena

Continuous glucose monitoring (CGM) is a minimally invasive technology that measures blood glucose every few minutes for weeks or months at a time. CGM data are often collected in the free-living environment and is strongly related to…

Methodology · Statistics 2025-09-04 Marcos Matabuena , Ciprian M. Crainiceanu

Diabetes is one of the deadliest diseases in the world and affects nearly 10 percent of the global adult population. Fortunately, powerful new technologies allow for a consistent and reliable treatment plan for people with diabetes. One…

Other Quantitative Biology · Quantitative Biology 2021-01-08 Julia Ann Jose , Trae Waggoner , Sudarsan Manikandan

Continuous Glucose Monitoring (CGM) has enabled important opportunities for diabetes management. This study explores the use of CGM data as input for digital decision support tools. We investigate how Recurrent Neural Networks (RNNs) can be…

A task of vital clinical importance, within Diabetes management, is the prevention of hypo/hyperglycemic events. Increasingly adopted Continuous Glucose Monitoring (CGM) devices offer detailed, non-intrusive and real time insights into a…

Machine Learning · Computer Science 2023-03-09 Jakub J. Dylag

Continuous glucose monitoring (CGM) combined with AI offers new opportunities for proactive diabetes management through real-time glucose forecasting. However, most existing models are task-specific and lack generalization across patient…

Quantitative Methods · Quantitative Biology 2025-08-04 Junjie Luo , Abhimanyu Kumbara , Mansur Shomali , Rui Han , Anand Iyer , Ritu Agarwal , Gordon Gao

Continuous glucose monitoring (CGM) data has revolutionized the management of type 1 diabetes, particularly when integrated with insulin pumps to mitigate clinical events such as hypoglycemia. Recently, there has been growing interest in…

Machine learning shows remarkable success for recognizing patterns in data. Here we apply the machine learning (ML) for the diagnosis of early stage diabetes, which is known as a challenging task in medicine. Blood glucose levels are…

Quantitative Methods · Quantitative Biology 2021-02-24 Woo Seok Lee , Junghyo Jo , Taegeun Song

The increasing number of diabetic patients is a serious issue in society today, which has significant negative impacts on people's health and the country's financial expenditures. Because diabetes may develop into potential serious…

Artificial Intelligence · Computer Science 2024-04-18 Ziyi Zhou , Ming Cheng , Yanjun Cui , Xingjian Diao , Zhaorui Ma

In the world today, diabetic complications are a major factor in the disease's high mortality rate. Diabetes mellitus has been a major source of concern for decades due to its global prevalence and the resulting rising costs to individuals,…

Medical Physics · Physics 2023-10-18 Umme Hafsa Momy

Precise glucose level monitoring is critical for people with diabetes to avoid serious complications. While there are several methods for continuous glucose level monitoring, research on maintenance devices is limited. To mitigate the gap,…

Machine Learning · Computer Science 2024-06-10 Azmine Toushik Wasi

This article compares ten recently proposed neural networks and proposes two ensemble neural network-based models for blood glucose prediction. All of them are tested under the same dataset, preprocessing workflow, and tools using the…

Quantitative Methods · Quantitative Biology 2021-09-07 Felix Tena , Oscar Garnica , Juan Lanchares , J. Ignacio Hidalgo

As continuous glucose monitors (CGMs) are used increasingly by diabetic patients, new and intuitive tools are needed to help patients and their physicians use these streams of data to improve blood glucose management. In this paper, we…

Quantitative Methods · Quantitative Biology 2013-05-15 Edward Aboufadel

Biosensor data has the potential ability to improve disease control and detection. However, the analysis of these data under free-living conditions is not feasible with current statistical techniques. To address this challenge, we introduce…

Applications · Statistics 2021-03-30 Marcos Matabuena , Alexander Petersen , Juan C. Vidal , Francisco Gude

Type 1 Diabetes (T1D) is an autoimmune disease leading to insulin insufficiency. Thus, patients require lifelong insulin therapy, which has a side effect of hypoglycemia. Hypoglycemia is a critical state of decreased blood glucose levels…

Machine Learning · Computer Science 2026-01-21 Beyza Cinar , Louisa van den Boom , Maria Maleshkova

Type 1 Diabetes is a chronic autoimmune condition in which the immune system attacks and destroys insulin-producing beta cells in the pancreas, resulting in little to no insulin production. Insulin helps glucose in your blood enter your…

Quantitative Methods · Quantitative Biology 2025-02-04 Soon Jynn Chu , Nalaka Amarasiri , Sandesh Giri , Priyata Kafle

The classification of diabetes and prediabetes by static glucose thresholds obscures the pathophysiological dysglycemia heterogeneity, primarily driven by insulin resistance (IR), beta-cell dysfunction, and incretin deficiency. This review…

Machine Learning · Computer Science 2025-11-07 Ahmed A. Metwally , Heyjun Park , Yue Wu , Tracey McLaughlin , Michael P. Snyder

We develop a new model of insulin-glucose dynamics for forecasting blood glucose in type 1 diabetics. We augment an existing biomedical model by introducing time-varying dynamics driven by a machine learning sequence model. Our model…

Machine Learning · Statistics 2020-08-10 Andrew C. Miller , Nicholas J. Foti , Emily Fox
‹ Prev 1 2 3 10 Next ›