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Bretti / Preziosi / Natalini

Mathematical Models and Computer Simulations for Biomedical Applications

Medium: Buch
ISBN: 978-3-031-35714-5
Verlag: Springer Nature Switzerland
Erscheinungstermin: 17.08.2023
Lieferfrist: bis zu 10 Tage
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.

Produkteigenschaften


  • Artikelnummer: 9783031357145
  • Medium: Buch
  • ISBN: 978-3-031-35714-5
  • Verlag: Springer Nature Switzerland
  • Erscheinungstermin: 17.08.2023
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2023
  • Serie: SEMA SIMAI Springer Series
  • Produktform: Gebunden, HC runder Rücken kaschiert
  • Gewicht: 571 g
  • Seiten: 257
  • Format (B x H x T): 160 x 241 x 21 mm
  • Ausgabetyp: Kein, Unbekannt

Autoren/Hrsg.

Herausgeber

Bretti, Gabriella

Preziosi, Luigi

Natalini, Roberto

Palumbo, Pasquale

- 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.