| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNINA9911049083803321 |
|
|
Autore |
Chaplain M. A. J |
|
|
Titolo |
Mathematical Oncology / / by Mark A. J. Chaplain, Luigi Preziosi |
|
|
|
|
|
Pubbl/distr/stampa |
|
|
New York, NY : , : Springer New York : , : Imprint : Springer, , 2025 |
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Edizione |
[1st ed. 2025.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (1181 pages) |
|
|
|
|
|
|
Collana |
|
Interdisciplinary Applied Mathematics, , 2196-9973 ; ; 62 |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Biomathematics |
Immunology |
Internal medicine |
Physiology |
Mathematical and Computational Biology |
Internal Medicine |
Animal Physiology |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Nota di contenuto |
|
Preface -- Biology/Pathology of Cancer -- Modeling the Immune Response to Cancer -- Simple Models of Tumor Growth -- Modeling Avascular, Multicellular Spheroid Growth -- Pre-pattern Models of Tumor Growth -- Modeling Tumor-induced Angiogenesis -- Modeling Invasion and Metastasis -- Mechanical Models of Growth -- Index. |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
Cancer is a complex and devastating disease, responsible for millions of deaths worldwide each year. While traditional oncology focuses on diagnosis and treatment through medical, surgical, radiation and clinical techniques, mathematical oncology has emerged as a powerful discipline that applies mathematical modelling to understand cancer growth, spread, and response to treatment. This volume provides a comprehensive exploration of mathematical approaches in oncology, offering a deep dive into differential equation models and biomechanical models. From reaction-diffusion equations that capture tumour growth and spread, to mechanical models that examine cellular interactions within tissues and vessels, this book presents both analytical techniques and computational modelling approaches that enhance our understanding of cancer dynamics. This book serves as |
|
|
|
|
|
|
|
|
|
|
both a reference for researchers and a foundation for integrating mathematical oncology into university curricula. By bridging the gap between mathematics, biology, and clinical research, it highlights the crucial role of mathematical modelling in advancing cancer treatment strategies and improving patient outcomes. |
|
|
|
|
|
| |