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Book ; Online ; E-Book: Mathematical models of cancer and different therapies

Padmanabhan, Regina / Meskin, Nader / Al Moustafa, Ala-Eddin

unified framework

(Series in BioEngineering,)

2021

Abstract: This book provides a unified framework for various currently available mathematical models that are used to analyze progression and regression in cancer development, and to predict its dynamics with respect to therapeutic interventions. Accurate and ... ...

Author's details	Regina Padmanabhan, Nader Meskin, Ala-Eddin Al Moustafa
Series title	Series in BioEngineering,
Abstract	This book provides a unified framework for various currently available mathematical models that are used to analyze progression and regression in cancer development, and to predict its dynamics with respect to therapeutic interventions. Accurate and reliable model representations of cancer dynamics are milestones in the field of cancer research. Mathematical modeling approaches are becoming increasingly common in cancer research, as these quantitative approaches can help to validate hypotheses concerning cancer dynamics and thus elucidate the complexly interlaced mechanisms involved. Even though the related conceptual and technical information is growing at an exponential rate, the application of said information and realization of useful healthcare devices are lagging behind. In order to remedy this discrepancy, more interdisciplinary research works and course curricula need to be introduced in academic, industrial, and clinical organizations alike. To that end, this book reformulates most of the existing mathematical models as special cases of a general model, allowing readers to easily get an overall idea of cancer dynamics and its modeling. Moreover, the book will help bridge the gap between biologists and engineers, as it brings together cancer dynamics, the main steps involved in mathematical modeling, and control strategies developed for cancer management. This also allows readers in both medical and engineering fields to compare and contrast all the therapy-based models developed to date using a single source, and to identify unexplored research directions.
Keywords	Cancer/Mathematical models
Subject code	616.99400113
Language	English
Size	1 online resource (XVI, 256 p. 35 illus., 29 illus. in color.)
Edition	1st ed. 2021.
Publisher	Springer
Publishing place	Gateway East, Singapore
Document type	Book ; Online ; E-Book
Remark	Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
ISBN	981-15-8640-3 ; 981-15-8639-X ; 978-981-15-8640-8 ; 978-981-15-8639-2
DOI	10.1007/978-981-15-8640-8
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Article ; Online: Deep reinforcement learning-based control of chemo-drug dose in cancer treatment.

Mashayekhi, Hoda / Nazari, Mostafa / Jafarinejad, Fatemeh / Meskin, Nader

Computer methods and programs in biomedicine

2023 Volume 243, Page(s) 107884

Abstract: Background and objective: Advancement in the treatment of cancer, as a leading cause of death worldwide, has promoted several research activities in various related fields. The development of effective treatment regimens with optimal drug dose ... ...

Abstract	Background and objective: Advancement in the treatment of cancer, as a leading cause of death worldwide, has promoted several research activities in various related fields. The development of effective treatment regimens with optimal drug dose administration using a mathematical modeling framework has received extensive research attention during the last decades. However, most of the control techniques presented for cancer chemotherapy are mainly model-based approaches. The available model-free techniques based on Reinforcement Learning (RL), commonly discretize the problem states and variables, which other than demanding expert supervision, cannot model the real-world conditions accurately. The more recent Deep Reinforcement Learning (DRL) methods, which enable modeling the problem in its original continuous space, are rarely applied in cancer chemotherapy. Methods: In this paper, we propose an effective and robust DRL-based, model-free method for the closed-loop control of cancer chemotherapy drug dosing. A nonlinear pharmacological cancer model is used for simulating the patient and capturing the cancer dynamics. In contrast to previous work, the state variables and control action are modeled in their original infinite spaces to avoid expert-guided discretization and provide a more realistic solution. The DRL network is trained to automatically adjust the drug dose based on the monitored states of the patient. The proposed method provides an adaptive control technique to respond to the special conditions and diagnosis measurements of different categories of patients. Results and conclusions: The performance of the proposed DRL-based controller is evaluated by numerical analysis of different diverse simulated patients. Comparison to the state-of-the-art RL-based method, which uses discretized state and action spaces, shows the superiority of the approach in the process and duration of cancer chemotherapy treatment. In the majority of the studied cases, the proposed model decreases the medication period and the total amount of administrated drug, while increasing the rate of reduction in tumor cells.
MeSH term(s)	Humans ; Learning ; Neoplasms/drug therapy
Language	English
Publishing date	2023-10-24
Publishing country	Ireland
Document type	Journal Article
ZDB-ID	632564-6
ISSN	1872-7565 ; 0169-2607
ISSN (online)	1872-7565
ISSN	0169-2607
DOI	10.1016/j.cmpb.2023.107884
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Article ; Online: Data-driven fault detection and isolation of nonlinear systems using deep learning for Koopman operator.

Bakhtiaridoust, Mohammadhosein / Yadegar, Meysam / Meskin, Nader

ISA transactions

2022 Volume 134, Page(s) 200–211

Abstract: This paper proposes a data-driven actuator fault detection and isolation approach for the general class of nonlinear systems. The proposed method uses a deep neural network architecture to obtain an invariant set of basis functions for the Koopman ... ...

Abstract	This paper proposes a data-driven actuator fault detection and isolation approach for the general class of nonlinear systems. The proposed method uses a deep neural network architecture to obtain an invariant set of basis functions for the Koopman operator to form a linear Koopman predictor for a nonlinear system. Then, the obtained linear model is used for fault detection and isolation purposes without relying on prior knowledge about the underlying dynamics. Moreover, a recursive method is proposed for fault detection and isolation that is entirely data-driven with the key feature of global validity for the system's whole operating region due to the Koopman operator's global characteristic. Finally, the approach's efficacy is demonstrated using two simulations on a coupled nonlinear system and a two-link manipulator benchmark.
Language	English
Publishing date	2022-09-05
Publishing country	United States
Document type	Journal Article
ZDB-ID	2012746-7
ISSN	1879-2022 ; 0019-0578
ISSN (online)	1879-2022
ISSN	0019-0578
DOI	10.1016/j.isatra.2022.08.030
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Book ; Online: Safe Control Synthesis Using Environmentally Robust Control Barrier Functions

Hamdipoor, Vahid / Meskin, Nader / Cassandras, Christos G.

2023

Abstract: In this paper, we study a safe control design for dynamical systems in the presence of uncertainty in a dynamical environment. The worst-case error approach is considered to formulate robust Control Barrier Functions (CBFs) in an optimization-based ... ...

Abstract	In this paper, we study a safe control design for dynamical systems in the presence of uncertainty in a dynamical environment. The worst-case error approach is considered to formulate robust Control Barrier Functions (CBFs) in an optimization-based control synthesis framework. It is first shown that environmentally robust CBF formulations result in second-order cone programs (SOCPs). Then, a novel scheme is presented to formulate robust CBFs which takes the nominally safe control as its desired control input in optimization-based control design and then tries to minimally modify it whenever the robust CBF constraint is violated. This proposed scheme leads to quadratic programs (QPs) which can be easily solved. Finally, the effectiveness of the proposed approach is demonstrated on an adaptive cruise control example.
Keywords	Electrical Engineering and Systems Science - Systems and Control
Publishing date	2023-04-23
Publishing country	us
Document type	Book ; Online
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Article: HVAC system attack detection dataset

Elnour, Mariam / Meskin, Nader / Khan, Khaled / Jain, Raj

Data in Brief. 2021 Aug., v. 37

2021

Abstract: The importance of the security of building management systems (BMSs) has increased given the advances in the technologies used. Since the Heating, Ventilation, and Air Conditioning (HVAC) system in buildings accounts for about 40% of the total energy ... ...

Abstract	The importance of the security of building management systems (BMSs) has increased given the advances in the technologies used. Since the Heating, Ventilation, and Air Conditioning (HVAC) system in buildings accounts for about 40% of the total energy consumption, threats targeting the HVAC system can be quite severe and costly. Given the limitations on accessing a real HVAC system for research purposes and the unavailability of public labeled datasets to investigate the cybersecurity of HVAC systems, this paper presents a dataset of a 12-zone HVAC system that was collected from a simulation model using the Transient System Simulation Tool (TRNSYS). It aims to promote and support the research in the field of cybersecurity of HVAC systems in smart buildings [1] by facilitating the validation of attack detection and mitigation strategies, benchmarking the performance of different data-driven algorithms, and studying the impact of attacks on the HVAC system.
Keywords	air ; computer security ; data collection ; energy ; heat ; simulation models
Language	English
Dates of publication	2021-08
Publishing place	Elsevier Inc.
Document type	Article
ZDB-ID	2786545-9
ISSN	2352-3409
ISSN	2352-3409
DOI	10.1016/j.dib.2021.107166
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: HVAC system attack detection dataset.

Elnour, Mariam / Meskin, Nader / Khan, Khaled / Jain, Raj

Data in brief

2021 Volume 37, Page(s) 107166

Abstract	The importance of the security of building management systems (BMSs) has increased given the advances in the technologies used. Since the Heating, Ventilation, and Air Conditioning (HVAC) system in buildings accounts for about 40% of the total energy consumption, threats targeting the HVAC system can be quite severe and costly. Given the limitations on accessing a real HVAC system for research purposes and the unavailability of public labeled datasets to investigate the cybersecurity of HVAC systems, this paper presents a dataset of a 12-zone HVAC system that was collected from a simulation model using the Transient System Simulation Tool (TRNSYS). It aims to promote and support the research in the field of cybersecurity of HVAC systems in smart buildings [1] by facilitating the validation of attack detection and mitigation strategies, benchmarking the performance of different data-driven algorithms, and studying the impact of attacks on the HVAC system.
Language	English
Publishing date	2021-05-28
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2786545-9
ISSN	2352-3409 ; 2352-3409
ISSN (online)	2352-3409
ISSN	2352-3409
DOI	10.1016/j.dib.2021.107166
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Article ; Online: A Path towards Timely VAP Diagnosis: Proof-of-Concept Study on Pyocyanin Sensing with Cu-Mg Doped Graphene Oxide.

Noorizadeh, Mohammad / Geetha, Mithra / Bensaali, Faycal / Meskin, Nader / Sadasivuni, Kishor K / Zughaier, Susu M / Elgamal, Mahmoud / Ait Hssain, Ali

Biosensors

2024 Volume 14, Issue 1

Abstract: In response to the urgent requirement for rapid, precise, and cost-effective detection in intensive care units (ICUs) for ventilated patients, as well as the need to overcome the limitations of traditional detection methods, researchers have turned their ...

Abstract	In response to the urgent requirement for rapid, precise, and cost-effective detection in intensive care units (ICUs) for ventilated patients, as well as the need to overcome the limitations of traditional detection methods, researchers have turned their attention towards advancing novel technologies. Among these, biosensors have emerged as a reliable platform for achieving accurate and early diagnoses. In this study, we explore the possibility of using Pyocyanin analysis for early detection of pathogens in ventilator-associated pneumonia (VAP) and lower respiratory tract infections in ventilated patients. To achieve this, we developed an electrochemical sensor utilizing a graphene oxide-copper oxide-doped MgO (
MeSH term(s)	Humans ; Pyocyanine ; Pneumonia, Ventilator-Associated ; Copper ; Magnesium Oxide ; Graphite
Chemical Substances	Pyocyanine (9OQM399341) ; graphene oxide ; Copper (789U1901C5) ; Magnesium Oxide (3A3U0GI71G) ; Graphite (7782-42-5)
Language	English
Publishing date	2024-01-16
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662125-3
ISSN	2079-6374 ; 2079-6374
ISSN (online)	2079-6374
ISSN	2079-6374
DOI	10.3390/bios14010048
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Article ; Online: Ambulatory extracorporeal membrane oxygenation simulator: The next frontier in clinical training.

Sayed, Aya N / Noorizadeh, Mohammad / Alhomsi, Yahya / Bensaali, Faycal / Meskin, Nader / Ait Hssain, Ali

Perfusion

2023 , Page(s) 2676591231201527

Abstract: Background: Current medical simulators for extracorporeal membrane oxygenation (ECMO) are expensive and rely on low-fidelity methodologies. This creates a challenge that demands a new approach to eliminate high costs and integrate with critical care ... ...

Abstract	Background: Current medical simulators for extracorporeal membrane oxygenation (ECMO) are expensive and rely on low-fidelity methodologies. This creates a challenge that demands a new approach to eliminate high costs and integrate with critical care environments, especially in light of the scarce resources and supplies available after the COVID-19 pandemic. Methods: To address this challenge, we examined the current state-of-the-art medical simulators and collaborated closely with Hamad Medical Corporation (HMC), the primary healthcare provider in Qatar, to establish criteria for advancing the cutting-edge ECMO simulation. This article presents a comprehensive ambulatory high-realism and cost-effective ECMO simulator. Results: Over the past 3 years, we have surveyed relevant literature, gathered data, and continuously developed a prototype of the system modules and the accompanying tablet application. By doing so, we have successfully addressed the issue of cost and fidelity in ECMO simulation, providing an effective tool for medical professionals to improve their understanding and treatment of patients requiring ECMO support. Conclusions: This paper will focus on presenting an overall ambulatory ECMO simulator, detailing the various sub-systems and emphasizing the modular casing of the physical components and the simulated patient monitor.
Language	English
Publishing date	2023-09-14
Publishing country	England
Document type	Journal Article
ZDB-ID	645038-6
ISSN	1477-111X ; 0267-6591
ISSN (online)	1477-111X
ISSN	0267-6591
DOI	10.1177/02676591231201527
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Book ; Online: Sensor Fault Detection and Isolation via Networked Estimation

Doostmohammadian, Mohammadreza / Meskin, Nader

Full-Rank Dynamical Systems

2020

Abstract: This paper considers the problem of simultaneous sensor fault detection, isolation, and networked estimation of linear full-rank dynamical systems. The proposed networked estimation is a variant of single time-scale protocol and is based on (i) consensus ...

Abstract	This paper considers the problem of simultaneous sensor fault detection, isolation, and networked estimation of linear full-rank dynamical systems. The proposed networked estimation is a variant of single time-scale protocol and is based on (i) consensus on \textit{a-priori} estimates and (ii) measurement innovation. The necessary connectivity condition on the sensor network and stabilizing block-diagonal gain matrix is derived based on our previous works. Considering additive faults in the presence of system and measurement noise, the estimation error at sensors is derived and proper residuals are defined for fault detection. Unlike many works in the literature, no simplifying upper-bound condition on the noise is considered and we assume Gaussian system/measurement noise. A probabilistic threshold is then defined for fault detection based on the estimation error covariance norm. Finally, a graph-theoretic sensor replacement scenario is proposed to recover possible loss of networked observability due to removing the faulty sensor. We examine the proposed fault detection and isolation scheme on an illustrative academic example to verify the results and make a comparison study with related literature.
Keywords	Electrical Engineering and Systems Science - Systems and Control ; Computer Science - Multiagent Systems
Subject code	003
Publishing date	2020-09-25
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Finite-Time Stability Under Denial of Service

Doostmohammadian, Mohammadreza / Meskin, Nader

2020

Abstract: Finite-time stability of networked control systems under Denial of Service (DoS) attacks are investigated in this paper, where the communication between the plant and the controller is compromised at some time intervals. Toward this goal, first an event- ... ...

Abstract	Finite-time stability of networked control systems under Denial of Service (DoS) attacks are investigated in this paper, where the communication between the plant and the controller is compromised at some time intervals. Toward this goal, first an event-triggered mechanism based on the variation rate of the Lyapunov function is proposed such that the closed-loop system remains finite-time stable (FTS) and at the same time, the amount data exchange in the network is reduced. Next, the vulnerability of the proposed event-triggered finite-time controller in the presence of DoS attacks are evaluated and sufficient conditions on the DoS duration and frequency are obtained to assure the finite-time stability of the closed-loop system in the presence of DoS attack where no assumption on the DoS attack in terms of following a certain probabilistic or a well-structured periodic model is considered. Finally, the efficiency of the proposed approach is demonstrated through a simulation study.
Keywords	Electrical Engineering and Systems Science - Systems and Control
Publishing date	2020-05-03
Publishing country	us
Document type	Book ; Online
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