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Objective: As metabolic cost is a primary factor influencing humans' gait, we want to deepen our understanding of metabolic energy expenditure models. Therefore, this paper identifies the parameters and input variables, such as muscle or…

Machine Learning · Computer Science 2023-11-08 Markus Gambietz , Marlies Nitschke , Jörg Miehling , Anne Koelewijn

Diabetes mellitus (DM) is a global health issue of significance that must be diagnosed as early as possible and managed well. This study presents a framework for diabetes prediction using Machine Learning (ML) models, complemented with…

Machine Learning · Computer Science 2025-02-13 Pir Bakhsh Khokhar , Viviana Pentangelo , Fabio Palomba , Carmine Gravino

Diabetes mellitus is a global health crisis characterized by poor blood sugar regulation, impacting millions of people worldwide and leading to severe complications and mortality. Although Type 1 Diabetes Mellitus (T1DM) has a lower number…

Other Quantitative Biology · Quantitative Biology 2025-04-14 Rinrada Jadsadaphongphaibool , Dadi Bi , Christian D. Lorenz , Yansha Deng , Robert Schober

This paper presents a comprehensive survey of various established mathematical models pertaining to Somitogenesis, a biological process. The study begins by revisiting and replicating the findings from prominent research papers in this…

Dynamical Systems · Mathematics 2023-10-09 Hanyu Song

Obesity rates have been increasing over recent decades, causing significant concern among policy makers. Excess body fat, commonly measured by body mass index (BMI), is a major risk factor for several common disorders including diabetes and…

Applications · Statistics 2014-12-12 Keming Yu , Rahim Alhamzawi , Frauke Becker , Joanne Lord

Cell cultures exhibit rich and complex behaviors driven by dynamic metabolic interactions among cells. In this work, we present a model that captures these interactions through a framework inspired by statistical mechanics. Using Monte…

Biological Physics · Physics 2025-09-25 A. R. Batista-Tomás , C. Díaz-Faloh , R. Mulet

High-throughput metabolomics investigations, when conducted in large human cohorts, represent a potentially powerful tool for elucidating the biochemical diversity and mechanisms underlying human health and disease. Large-scale metabolomics…

Globally, the number of obese patients has doubled due to sedentary lifestyles and improper dieting. The tremendous increase altered human genetics, and health. According to the world health organization, Life expectancy dropped from 80 to…

Quantitative Methods · Quantitative Biology 2022-08-08 Amin Gasmi

Mathematical modeling in cancer has been growing in popularity and impact since its inception in 1932. The first theoretical mathematical modeling in cancer research was focused on understanding tumor growth laws and has grown to include…

Tissues and Organs · Quantitative Biology 2013-05-22 Jacob G. Scott , Philip Gerlee , David Basanta , Alexander G. Fletcher , Philip K. Maini , Alexander RA Anderson

Progress in the biomedical field through the use of deep learning is hindered by the lack of interpretability of the models. In this paper, we study the RETAIN architecture for the forecasting of future glucose values for diabetic people.…

Machine Learning · Computer Science 2020-09-11 Maxime De Bois , Mounîm A. El Yacoubi , Mehdi Ammi

The author describes some of his experiences as a mathematician cooperating with diabetes specialists.

History and Overview · Mathematics 2013-12-10 Bernhelm Booss-Bavnbek

The Bergman minimal model is a dynamic model of plasma glucose concentration. It has two input variables -- insulin delivery and carbohydrate intake. We investigate the behaviour of plasma glucose concentration predicted by the model given…

Optimization and Control · Mathematics 2017-03-10 Christopher Townsend , Maria M. Seron , Graham C. Goodwin

Accurately estimating parameters of physiological models is essential to achieving reliable digital twins. For Type 1 Diabetes, this is particularly challenging due to the complexity of glucose-insulin interactions. Traditional methods…

Previous likelihood-based linear modeling of nutritional data has been limited by the availability of software that allows flexible error structures in the data. We demonstrate the use of a Bayesian modeling approach to the analysis of such…

Statistics Theory · Mathematics 2007-06-13 Andrew Lawson , Daniela Nitcheva

The paper deals with the developing of the methodological backgrounds for the modeling and simulation of complex dynamical objects. Such backgrounds allow us to perform coordinate transformation and formulate the algorithm of its usage for…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-07 Roman Voliansky , Andri Pranolo

We offer an insight into our mathematical endeavors, which aim to advance the foundational understanding of energy systems in a broad context, encompassing facets such as charge transport, energy storage, markets, and collective behavior.…

General Mathematics · Mathematics 2024-12-30 Nicklas Jävergård , Grigor Nika , Adrian Muntean

Over the last two decades, the science has come a long way from relying on only physical experiments and observations to experimentation using computer simulators. This chapter focusses on the modelling and analysis of data arising from…

Methodology · Statistics 2020-12-22 M. Harshvardhan , Pritam Ranjan

The macroscopic behavior of the solution of a coupled system of partial differential equations arising in the modeling of reaction-diffusion processes in periodic porous media is analyzed. Our mathematical model can be used for studying…

Analysis of PDEs · Mathematics 2019-06-19 G. Cardone , C. Perugia , C. Timofte

Postprandial hyperglycemia, marked by the blood glucose level exceeding the normal range after consuming a meal, is a critical indicator of progression toward type 2 diabetes in people with prediabetes and in healthy individuals. A key…

Monitoring dietary habits is crucial for preventing health risks associated with overeating and undereating, including obesity, diabetes, and cardiovascular diseases. Traditional methods for tracking food intake rely on self-reported data…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Wallace Lee , YuHao Chen