Mathematical Models and Computer Simulations for Biomedical Applications (Sema Simai Springer Series)

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Mathematical Models and Computer Simulations for Biomedical Applications (Sema Simai Springer Series)

Bretti, Gabriella (EDT)/ Natalini, Roberto (EDT)/ Palumbo, Pasquale (EDT)

ウェブストア価格 ¥51,741（本体¥47,038）
Springer International Publishing AG（2023/08発売）
外貨定価 US$ 249.99
ポイント 470pt

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製本 Hardcover:ハードカバー版／ページ数 257 p.
商品コード 9783031357145

Full Description

Mathematical modelling and computer simulations are playing a crucial role in the solution of the complex problems arising in the field of biomedical sciences and provide a support to clinical and experimental practices in an interdisciplinary framework.
Indeed, the development of mathematical models and efficient numerical simulation tools is of key importance when dealing with such applications.
Moreover, since the parameters in biomedical models have peculiar scientific interpretations and their values are often unknown, accurate estimation techniques need to be developed for parameter identification against the measured data of observed phenomena. In the light of the new challenges brought by the biomedical applications, computational mathematics paves the way for the validation of the mathematical models and the investigation of control problems.
The volume hosts high-quality selected contributions containing original research results as well as comprehensive papers and survey articles including prospective discussion focusing on some topical biomedical problems. It is addressed, but not limited to: research institutes, academia, and pharmaceutical industries.

- An Application of the Grünwald-Letinkov Fractional Derivative to a Study of Drug Diffusion in Pharmacokinetic Compartmental Models. - Merging On-chip and In-silico Modelling for Improved Understanding of Complex Biological Systems. - A Particle Model to Reproduce Collective Migration and Aggregation of Cells with Different Phenotypes. - Modelling HIF-PHD Dynamics and Related Downstream Pathways. - An Imaging-Informed Mechanical Framework to Provide a Quantitative Description of Brain Tumour Growth and the Subsequent Deformation of White Matter Tracts. - A Multi-Scale Immune System Simulator for the Onset of Type 2 Diabetes. - Molecular Fingerprint Based and Machine Learning Driven QSAR for Bioconcentration Pathways Determination. - Advanced Models for COVID-19 Variant Dynamics and Pandemic Waves. - Multifractal Spectrum Based Classification for Breast Cancer.