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Mathematics
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Mathematics in Biomedicine, 2nd Edition
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Mathematics in Biomedicine, 2nd Edition

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematical Biology".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 4365

Special Issue Editors

Dr. Maria Laura Manca

E-Mail Website
Guest Editor
Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
Interests: biomathematics; biostatistics; biomedical signals; mathematical neuroscience; mathematical music
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Vladimir Simeonov Gueorguiev

E-Mail Website
Guest Editor
Department of Mathematics, University of Pisa, Pisa, Italy
Interests: inverse scattering problems; nonlinear equations of quantum mechanics; nonlinear waves in gravitation; hyperbolic PDE; stability of solitary waves
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The field of biomathematics includes a broad range of scales and levels of biological organization. The main goal of this Special Issue is to celebrate the huge increase in and relevance of applications of mathematics to biology and life sciences.

Editors will accept high-quality papers with original research in all fields of applications of mathematics to biology and medicine.

Dr. Maria Laura Manca
Prof. Dr. Vladimir Simeonov Gueorguiev
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 epidemiology
  • mathematics neuroscience
  • mathematical oncology
  • biomathematics

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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Research

19 pages, 4989 KiB  
Article
Multi-Drug Scheduling for Chemotherapy Using Fractional Order Internal Model Controller
by Nikhil Pachauri, Velamuri Suresh, MVV Prasad Kantipudi, Reem Alkanhel and Hanaa A. Abdallah
Mathematics 2023, 11(8), 1779; https://doi.org/10.3390/math11081779 - 8 Apr 2023
Cited by 6 | Viewed by 1698
Abstract
Chemotherapy is a widely used cancer treatment method globally. However, cancer cells can develop resistance towards single-drug-based chemotherapy if it is infused for extended periods, resulting in treatment failure in many cases. To address this issue, oncologists have progressed towards using multi-drug chemotherapy [...] Read more.
Chemotherapy is a widely used cancer treatment method globally. However, cancer cells can develop resistance towards single-drug-based chemotherapy if it is infused for extended periods, resulting in treatment failure in many cases. To address this issue, oncologists have progressed towards using multi-drug chemotherapy (MDC). This method considers different drug concentrations for cancer treatment, but choosing incorrect drug concentrations can adversely affect the patient’s body. Therefore, it is crucial to recognize the trade-off between drug concentrations and their adverse effects. To address this issue, a closed-loop multi-drug scheduling based on Fractional Order Internal-Model-Control Proportional Integral (IMC-FOPI) Control is proposed. The proposed scheme combines the benefits of fractional PI and internal model controllers. Additionally, the parameters of IMC-FOPI are optimally tuned using a random walk-based Moth-flame optimization. The performance of the proposed controller is compared with PI and Two degrees of freedom PI (2PI) controllers for drug concentration control at the tumor site. The results reveal that the proposed control scheme improves the settling time by 43% and 21% for VX, 54% and 48 % for VY, and 48% and 40% for VZ, respectively, compared to PI and 2PI. Therefore, it can be concluded that the proposed control scheme is more efficient in scheduling multi-drug than conventional controllers. Full article
(This article belongs to the Special Issue Mathematics in Biomedicine, 2nd Edition)
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22 pages, 1840 KiB  
Article
Weighted Log-Rank Test for Clinical Trials with Delayed Treatment Effect Based on a Novel Hazard Function Family
by Kaihuan Qian and Xiaohua Zhou
Mathematics 2022, 10(15), 2573; https://doi.org/10.3390/math10152573 - 25 Jul 2022
Cited by 2 | Viewed by 1850
Abstract
In clinical trials with delayed treatment effect, the standard log-rank method in testing the difference between survival functions may have problems, including low power and poor robustness, so the method of weighted log-rank test (WLRT) is developed to improve the test performance. In [...] Read more.
In clinical trials with delayed treatment effect, the standard log-rank method in testing the difference between survival functions may have problems, including low power and poor robustness, so the method of weighted log-rank test (WLRT) is developed to improve the test performance. In this paper, a hyperbolic-cosine-shaped (CH) hazard function family model is proposed to simulate delayed treatment effect scenarios. Then, based on Fleming and Harrington’s method, this paper derives the corresponding weight function and its regular corrections, which are powerful in test, theoretically. Alternative methods of parameters selection based on potential information are also developed. Further, the simulation study is conducted to compare the power performance between CH WLRT, classical WLRT, modest weighted log-rank test and WLRT with logistic-type weight function under different hazard scenarios and simulation settings. The results indicate that the CH statistics are powerful and robust in testing the late difference, so the CH test is useful and meaningful in practice. Full article
(This article belongs to the Special Issue Mathematics in Biomedicine, 2nd Edition)
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