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Precise and timely forecasting of blood glucose levels is essential for effective diabetes management. While extensive research has been conducted on Type 1 diabetes mellitus, Type 2 diabetes mellitus (T2DM) presents unique challenges due…

Computational Engineering, Finance, and Science · Computer Science 2024-09-12 Yuyang Sun , Panagiotis Kosmas

Background and objective: Diabetes is one of the four leading causes of death worldwide, necessitating daily blood glucose monitoring. While sweat offers a promising non-invasive alternative for glucose monitoring, its application remains…

Quantitative Methods · Quantitative Biology 2024-12-05 Xiaoyu Yin , Elisabetta Peri , Eduard Pelssers , Jaap den Toonder , Lisa Klous , Hein Daanen , Massimo Mischi

Diabetes mellitus is a complex group of syndromes that have in common a disturbance in the body's use of glucose, resulting in an elevated blood sugar. Once detected, sugar diabetes can be controlled by an appropriate regimen that should…

Medical Physics · Physics 2008-11-03 Raju Poddar , Joseph Thomas Andrews , Pratyoosh Shukla , Pratima Sen

Background: Type 2 diabetes mellitus (T2DM) is increasingly recognised as a systemic disease characterised by coordinated dysfunction across metabolic, renal, lipid, and inflammatory pathways. Existing clinical assessments often fail to…

Machine Learning · Computer Science 2026-05-26 Mini Han Wang , Liting Huang , Wei Hong , Boonthawan Wingwon

Personal health devices can enable continuous monitoring of health parameters. However, the benefit of these devices is often directly related to the frequency of use. Therefore, adherence to personal health devices is critical. This paper…

Computers and Society · Computer Science 2020-06-11 Sudip Vhaduri , Temiloluwa Prioleau

Biomedical signals carry signature rhythms of complex physiological processes that control our daily bodily activity. The properties of these rhythms indicate the nature of interaction dynamics among physiological processes that maintain a…

Machine Learning · Computer Science 2020-12-14 Yassin Khalifa , Danilo Mandic , Ervin Sejdić

In routine care, individuals identified a priori as high-risk are usually tested for conditions more frequently. Protected attributes, such as sex or ethnicity may also determine testing frequency. Such heterogeneous detection rates across…

Applications · Statistics 2026-05-08 Jose Benitez-Aurioles , Ricardo Silva , Brian McMillan , Matthew Sperrin

We conduct a review to assess how the simulation of repeated or recurrent events are planned. For such multivariate time-to-events, it is well established that the underlying mechanism is likely to be complex and to involve in particular…

Applications · Statistics 2015-03-20 Juliette Pénichoux , Thierry Moreau , Aurélien Latouche

In this article we suggest a new statistical approach considering survival heterogeneity as a breakpoint model in an ordered sequence of time to event variables. The survival responses need to be ordered according to a numerical covariate.…

Applications · Statistics 2016-09-26 Olivier Bouaziz , Grégory Nuel

In biomedical settings, multitype recurrent events such as stroke and heart failure occur frequently, often concluding with a terminal event such as death. Understanding the links between these recurring and terminal events is fundamental…

Methodology · Statistics 2025-09-15 Mithun Kumar Acharjee , AKM Fazlur Rahman

Chronic diseases such as diabetes pose significant management challenges, particularly due to the risk of complications like hypoglycemia, which require timely detection and intervention. Continuous health monitoring through wearable…

Machine Learning · Computer Science 2026-01-08 Vaibhav Gupta , Florian Grensing , Beyza Cinar , Maria Maleshkova

In this paper, we study the problem of blood glucose forecasting and provide a deep personalized solution. Predicting blood glucose level in people with diabetes has significant value because health complications of abnormal glucose level…

Machine Learning · Computer Science 2021-09-08 Mohammadreza Armandpour , Brian Kidd , Yu Du , Jianhua Z. Huang

In this paper, we develop a graphical modeling framework for the inference of networks across multiple sample groups and data types. In medical studies, this setting arises whenever a set of subjects, which may be heterogeneous due to…

Clinical time-series forecasting is increasingly studied for decision support, yet standard aggregate metrics can obscure whether a model is actually useful for the task it is meant to serve. In safety-critical settings, low average error…

Machine Learning · Computer Science 2026-05-04 Alireza Namazi , Heman Shakeri

Objective: The design of an Artificial Pancreas (AP) to regulate blood glucose levels requires reliable control methods. Model Predictive Control has emerged as a promising approach for glycemia control. However, model--based control…

Optimization and Control · Mathematics 2022-02-02 Claudia Lopez-Zazueta , Øyvind Stavdahl , Anders Lyngvi Fougner

We study a random walk (Markov chain) in an unbounded planar domain whose boundary is described by two curves of the form $x_2 = a^+ x_1^{\beta^+}$ and $x_2 = -a^- x_1^{\beta^-}$, with $x_1 \geq 0$. In the interior of the domain, the random…

Probability · Mathematics 2022-02-15 Mikhail V. Menshikov , Aleksandar Mijatović , Andrew R. Wade

People with type 1 diabetes (T1D) lack the ability to produce the insulin their bodies need. As a result, they must continually make decisions about how much insulin to self-administer to adequately control their blood glucose levels.…

Machine Learning · Computer Science 2020-09-22 Ian Fox , Joyce Lee , Rodica Pop-Busui , Jenna Wiens

Diabetes Mellitus is a metabolic disorder which may result in severe and potentially fatal complications if not well-treated and monitored. In this study, a quantitative analysis of the data collected using CGM (Continuous Glucose…

Quantitative Methods · Quantitative Biology 2023-08-15 Giulia Elena Aliffi , Giovanni Nastasi , Vittorio Romano , Dario Pitocco , Alessandro Rizzi , Elvin J. Moore , Andrea De Gaetano

Daytime hypoglycemia should be accurately predicted to achieve normoglycemia and to avoid disastrous situations. Hypoglycemia, an abnormally low blood glucose level, is divided into daytime hypoglycemia and nocturnal hypoglycemia. Many…

Machine Learning · Statistics 2017-05-01 Miyeon Jung , You-Bin Lee , Sang-Man Jin , Sung-Min Park

In studies of recurrent events, joint modeling approaches are often needed to allow for potential dependent censoring by a terminal event such as death. Joint frailty models for recurrent events and death with an additional dependence…

Methodology · Statistics 2023-04-25 Marie Böhnstedt , Jutta Gampe , Monique A. A. Caljouw , Hein Putter