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Mathematics
Special Issues
Biomathematics: Modelling and Simulation
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Biomathematics: Modelling and Simulation

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Computational and Applied Mathematics".

Deadline for manuscript submissions: closed (30 December 2023) | Viewed by 3478

Special Issue Editors

Prof. Dr. Maria Hadjinicolaou

E-Mail Website
Guest Editor
Applied Mathematics Laboratory, School of Science and Technology, Hellenic Open University, 26335 Patras, Greece
Interests: blood flow; multiscale modeling; tumor growth; wave propagation and scattering; heat and mass transfer; partial differential equations; asymptotic analysis and special functions
Dr. Foteini Kariotou

E-Mail Website
Guest Editor
Applied Mathematics Laboratory, School of Science and Technology, Hellenic Open University, 26335 Patra, Greece
Interests: ellipsoidal geometry; brain imaging techniques MEG-EEG; mathematical modeling; cancer tumour growth; wave propagation and scattering

Special Issue Information

Dear Colleagues,

The need for interdisciplinary research is imperative when studying real phenomena, especially concerning complex biological or ecological systems. Mathematical modeling and simulations are ubiquitous in such research, as they synthesize experimental observation and theoretical interpretation. Biomathematics encompasses pure and applied mathematics, as well as statistics, operations research, scientific computing,  information science, mathematical biology and systems biology. Furthermore, the need to develop specific analytical and numerical tools for biomedical problems and ecological phenomena is also a driving force in the advancement of mathematical theory, methods and techniques in general.

In this Special Issue, we welcome contributions (original research articles and high-quality review articles) on recent developments in mathematical modeling and simulation that are related, but not limited, to the following fields:

  • Biomedical modeling based on analytical, numerical and experimental methods;
  • Modeling and simulations of  physical, chemical and biological processes;
  • Mathematical epidemiology;
  • Mathematical ecology;
  • Biofluids;
  • Immunology;
  • Biomechanics;
  • Bioinformatics;
  • Neurobiology;
  • Neuroinformatics;
  • Medical imaging systems.

These may involve: algorithm design, dynamic programming, graph theory, data processing, spectral theory and decision problems in biology. 

We look forward to receiving your contributions.

Prof. Dr. Maria Hadjinicolaou
Dr. Foteini Kariotou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • mathematical modelling in biomedical applications
  • mathematical epidemiology
  • mathematical ecology
  • biomedical fluid flows
  • bioinformatics
  • neuroinformatics
  • partial differential equations
  • integro-differential equations
  • variational methods
  • dynamical systems
  • computational and numerical methods

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Published Papers (2 papers)

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Research

15 pages, 4413 KiB  
Article
Rapid Estimation of Contact Stresses in Imageless Total Knee Arthroplasty
by Jun Young Kim, Muhammad Sohail and Heung Soo Kim
Mathematics 2023, 11(16), 3527; https://doi.org/10.3390/math11163527 - 15 Aug 2023
Cited by 3 | Viewed by 1396
Abstract
Total knee arthroplasty (TKA) is a surgical technique to replace damaged knee joints with artificial implants. Recently, the imageless TKA has brought a revolutionary improvement to the accuracy of implant placement and ease of surgical process. Based on key anatomical points on the [...] Read more.
Total knee arthroplasty (TKA) is a surgical technique to replace damaged knee joints with artificial implants. Recently, the imageless TKA has brought a revolutionary improvement to the accuracy of implant placement and ease of surgical process. Based on key anatomical points on the knee, the software guides the surgeon during the TKA procedure. However, the number of revision surgeries is increasing due to malalignment caused by registration error, resulting in imbalanced contact stresses that lead to failure of the TKA. Conventional stress analysis methods involve time-consuming and computationally demanding finite element analysis (FEA). In this work, a machine-learning-based approach estimates the contact pressure on the TKA implants. The machine learning regression model has been trained using FEA data. The optimal preprocessing technique was confirmed by the data without preprocessing, data divided by model size, and data divided by model size and optimal angle. Extreme gradient boosting, random forest, and extra trees regression models were trained to determine the optimal approach. The proposed method estimates the contact stress instantly within 10 percent of the maximum error. This has resulted in a significant reduction in computational costs. The efficiency and reliability of the proposed work have been validated against the published literature. Full article
(This article belongs to the Special Issue Biomathematics: Modelling and Simulation)
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13 pages, 717 KiB  
Article
Calculation Method and Application of Time-Varying Transmission Rate via Data-Driven Approach
by Yuqing Sun, Zhonghua Zhang and Yulin Sun
Mathematics 2023, 11(13), 2955; https://doi.org/10.3390/math11132955 - 2 Jul 2023
Viewed by 1356
Abstract
Most research about compartmental models of infection disease often consider the transmission rate as a constant, which is not ideal for the dynamic surveillance of infectious diseases. This study fully utilized continuously updated real-time epidemiological data and proposed a SEAIUHR model incorporating asymptomatic [...] Read more.
Most research about compartmental models of infection disease often consider the transmission rate as a constant, which is not ideal for the dynamic surveillance of infectious diseases. This study fully utilized continuously updated real-time epidemiological data and proposed a SEAIUHR model incorporating asymptomatic and symptomatic infectiousness, reported and unreported cases, inpatient and non-inpatient cases, and vaccine inoculation. This study proposed a novel approach based on our model to calculate the time-varying transmission rate with an under-report rate, vaccination efficiency, and relaxation of social distancing behavior. The proposed method was evaluated based on epidemiological data from the United States. The results suggest that using this approach to combine epidemiological data can provide a clearer understanding of the spread rule of epidemic, offering data support for subsequent related research. Full article
(This article belongs to the Special Issue Biomathematics: Modelling and Simulation)
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