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Computational Mathematics and Modelling for Diabetes / edited by Abdesslam Boutayeb, Mohamed E.N. Lamlili

Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Industrial and Applied MathematicsPublisher: Singapore : Springer Nature Singapore, 2025Publisher: Singapore : Imprint: Springer, 2025Edition: 1st ed. 2025Description: 1 Online-Ressource(XVIII, 339 p. 64 illus., 45 illus. in color.)ISBN:
  • 9789819619252
Subject(s): Additional physical formats: 9789819619245 | 9789819619269 | 9789819619276 | Erscheint auch als: 9789819619245 Druck-Ausgabe | Erscheint auch als: 9789819619269 Druck-Ausgabe | Erscheint auch als: 9789819619276 Druck-AusgabeDDC classification:
  • 003.3 23
DOI: DOI: 10.1007/978-981-96-1925-2Online resources: Summary: Chapter 1 A Systematic Review of Mathematical Models Dealing with Diabetes Population Dynamics -- Chapter 2 Mathematical Modelling for Glucose Homeostasis and Associated Mechanisms a State-of-the-Art Review -- Chapter 3 A Comprehensive Review of Mathematical and Data-driven Models in Glucose Homeostasis and Diabetes Pathways.Summary: This book is a theoretical and pragmatic tool that applies mathematical modelling in understanding and managing diabetes and related complications such as diabetes predisposition, diabetes onset, regular glycaemic monitoring, glycated haemoglobin HbA1c, diabetes homeostasis, gestational diabetes and other associated diseases and conditions. Chapters in the book provide mathematical models dealing with the dynamics of insulin/glucose, the evolution from pre-diabetes to diabetes without and with complications, gestational diabetes and the association between diabetes and benign prostatic hyperplasia. It also applies new methods such as data mining, machine learning and deep learning. By offering pragmatic examples and comprehensive reviews on mathematical models used for diabetes, this book is useful for advanced researchers, academic teachers, students, scientists and high pharmaceutical industry executives willing to start modelling.PPN: PPN: 1927327067Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SMA | ZDB-2-SXMS
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