Nenad Filipovic - Böcker

Computational Modeling in Bioengineering and Bioinformatics promotes complementary disciplines that hold great promise for the advancement of research and development in complex medical and biological systems, and in the environment, public health, drug design, and so on. It provides a common platform by bridging these two very important and complementary disciplines into an interactive and attractive forum. Chapters cover biomechanics and bioimaging, biomedical decision support system, data mining, personalized diagnoses, bio-signal processing, protein structure prediction, tissue and cell engineering, biomedical image processing, analysis and visualization, high performance computing and sports bioengineering.

The book's chapters are the result of many international projects in the area of bioengineering and bioinformatics done at the Research and Development Center for Bioengineering BioIRC and by the Faculty of Engineering at the University of Kragujevac, Serbia.

Presents recent advances at the crossroads of biomedical engineering and bioinformatics, one of the hottest areas in biomedical and clinical research Discusses a wide range of leading-edge research topics, including biomechanics and bioimaging, biomedical decision support systems, data mining, personalized diagnoses, bio-signal processing, protein structure prediction, tissue and cell engineering, amongst others Includes coverage of biomechanical, bioengineering and computational methods of treatment and diagnosis

Cardiovascular and Respiratory Bioengineering focuses on computational tools and modeling techniques in cardiovascular and respiratory systems that help develop bioengineered solutions. The book demonstrates how these technologies can be utilized in order to tackle diseases and medical issues. It provides practical guidance on how a bioengineering or medical problem can be modeled, along with which computational models can be used. Topics include computer modeling of Purkinje fibers with different electrical potential applied, modeling of cardiomyopathies caused by sarcomeric gene mutations, altered sarcomere function, perturbations in intracellular ion homeostasis, impaired myocardial energetics at reduced costs, and more.

The book also discusses blood flow through deformable blood vessels in human aorta, abdominal aortic aneurysm, carotid artery, coronary artery and plaque formation, along with content on stent deployment modeling and stent design and optimization techniques.

Features practical applications of cardiovascular and respiratory technology to counteract diseases Includes detailed steps for the modeling of cardiovascular and respiratory systems Explores a range of different modeling methods, including computational modeling, predictive modeling and multi-scale modeling Covers biological processes and biomechanics relevant to cardiovascular and respiratory bioengineering

Bioengineering is a broad-based engineering discipline that applies engineering principles and design to challenges in human health and medicine, dealing with bio-molecular and molecular processes, product design, sustainability and analysis of biological systems. Applications that benefit from bioengineering include medical devices, diagnostic equipment and biocompatible materials, amongst others. Computer Modeling in Bioengineering offers a comprehensive reference for a large number of bioengineering topics, presenting important computer modeling problems and solutions for research and medical practice. Starting with basic theory and fundamentals, the book progresses to more advanced methods and applications, allowing the reader to become familiar with different topics to the desired extent. It includes unique and original topics alongside classical computational modeling methods, and each application is structured to explain the physiological background, phenomena that are to be modeled, the computational methods used in the model, and solutions of typical cases. The accompanying software contains over 80 examples, enabling the reader to study a topic using the theory and examples, then run the software to solve the same, or similar examples, varying the model parameters within a given range in order to investigate the problem at greater depth. Tutorials also guide the user in further exploring the modeled problem; these features promote easier learning and will help lecturers with presentations.Computer Modeling in Bioengineering includes computational methods for modelling bones, tissues, muscles, cardiovascular components, cartilage, cells and cancer nanotechnology as well as many other applications. It bridges the gap between engineering, biology and medicine, and will appeal not only to bioengineering students, lecturers and researchers, but also medical students and clinical researchers.

A systematic overview of the quickly developing field of bioengineering—with state-of-the-art modeling software! Computational Modeling and Simulation Examples in Bioengineering provides a comprehensive introduction to the emerging field of bioengineering. It provides the theoretical background necessary to simulating pathological conditions in the bones, muscles, cardiovascular tissue, and cancers, as well as lung and vertigo disease. The methodological approaches used for simulations include the finite element, dissipative particle dynamics, and lattice Boltzman. The text includes access to a state-of-the-art software package for simulating the theoretical problems. In this way, the book enhances the reader's learning capabilities in the field of biomedical engineering. The aim of this book is to provide concrete examples of applied modeling in biomedical engineering. Examples in a wide range of areas equip the reader with a foundation of knowledge regarding which problems can be modeled with which numerical methods. With more practical examples and more online software support than any competing text, this book organizes the field of computational bioengineering into an accessible and thorough introduction. Computational Modeling and Simulation Examples in Bioengineering: Includes a state-of-the-art software package enabling readers to engage in hands-on modeling of the examples in the bookProvides a background on continuum and discrete modeling, along with equations and derivations for three key numerical methodsConsiders examples in the modeling of bones, skeletal muscles, cartilage, tissue engineering, blood flow, plaque, and moreExplores stent deployment modeling as well as stent design and optimization techniques Generates different examples of fracture fixation with respect to the advantages in medical practice applicationsComputational Modeling and Simulation Examples in Bioengineering is an excellent textbook for students of bioengineering, as well as a support for basic and clinical research. Medical doctors and other clinical professionals will also benefit from this resource and guide to the latest modeling techniques.

This book presents an overview of a variety of contemporary statistical, mathematical and computer science techniques which are used to further the knowledge in the medical domain. The authors focus on applying data mining to the medical domain, including mining the sets of clinical data typically found in patient’s medical records, image mining, medical mining, data mining and machine learning applied to generic genomic data and more.This work also introduces modeling behavior of cancer cells, multi-scale computational models and simulations of blood flow through vessels by using patient-specific models. The authors cover different imaging techniques used to generate patient-specific models. This is used in computational fluid dynamics software to analyze fluid flow. Case studies are provided at the end of each chapter.Professionals and researchers with quantitative backgrounds will find Computational Medicine in Data Mining and Modeling useful as a reference. Advanced-level students studying computer science, mathematics, statistics and biomedicine will also find this book valuable as a reference or secondary text book.

This book presents an overview of a variety of contemporary statistical, mathematical and computer science techniques which are used to further the knowledge in the medical domain. The authors focus on applying data mining to the medical domain, including mining the sets of clinical data typically found in patient’s medical records, image mining, medical mining, data mining and machine learning applied to generic genomic data and more.This work also introduces modeling behavior of cancer cells, multi-scale computational models and simulations of blood flow through vessels by using patient-specific models. The authors cover different imaging techniques used to generate patient-specific models. This is used in computational fluid dynamics software to analyze fluid flow. Case studies are provided at the end of each chapter.Professionals and researchers with quantitative backgrounds will find Computational Medicine in Data Mining and Modeling useful as a reference. Advanced-level students studying computer science, mathematics, statistics and biomedicine will also find this book valuable as a reference or secondary text book.

This book explores the latest and most relevant topics in the field of computational bioengineering and bioinformatics, with a particular focus on patient-specific, disease-progression modeling. It covers computational methods for cardiovascular disease prediction, with an emphasis on biomechanics, biomedical decision support systems, data mining, personalized diagnostics, bio-signal processing, protein structure prediction, biomedical image processing, analysis and visualization, and high-performance computing. It also discusses state-of-the-art tools for disease characterization, and recent advances in areas such as biomechanics, cardiovascular engineering, patient-specific modeling, population-based modeling, multiscale modeling, image processing, data mining, biomedical decision-support systems, signal processing, biomaterials and dental biomechanics, tissue and cell engineering, computational chemistry and high-performance computing. As such, it is a valuable resource for researchers, medical and bioengineering students, and medical device and software experts

This book explores the latest and most relevant topics in the field of computational bioengineering and bioinformatics, with a particular focus on patient-specific, disease-progression modeling. It covers computational methods for cardiovascular disease prediction, with an emphasis on biomechanics, biomedical decision support systems, data mining, personalized diagnostics, bio-signal processing, protein structure prediction, biomedical image processing, analysis and visualization, and high-performance computing. It also discusses state-of-the-art tools for disease characterization, and recent advances in areas such as biomechanics, cardiovascular engineering, patient-specific modeling, population-based modeling, multiscale modeling, image processing, data mining, biomedical decision-support systems, signal processing, biomaterials and dental biomechanics, tissue and cell engineering, computational chemistry and high-performance computing. As such, it is a valuable resource for researchers, medical and bioengineering students, and medical device and software experts

The book is covering knowledge and results in theory, methodology, and applications of artificial intelligence and machine learning in academia and industry.

This book aims at meeting the challenge of getting along with today’s unprecedented rate of innovation supported by disruptive digital technologies, which changed the perception of the productivity and effectiveness and opened a gateway to more than ever dynamic advances in solving the important societal challenges."Disruptive Information Technologies for a Smart Society" is the proceedings book of the 13th International conference for information society and technologies that brings together experts from various fields to discuss the latest advancements in software engineering, machine learning, digital water, and ICT for health and sport.The book and the conference serve as a platform for researchers of all career stages in technical sciences, especially Ph.D. students, practitioners, and industry experts in health care, energy, Fintech, AI, and other areas to share and learn on the cutting-edge technologies and stay at the forefront of these rapidly evolving fields.

This book covers in silico clinical trials of cardiovascular disease using a finite element and machine learning approach. Part I describes the fundamentals as well as the latest developments in the field: finite element modeling, system biology modeling for drug optimization, artificial intelligence approach for medical image processing, as well as pharmacokinetic and AI modeling. Part II provides use cases to describe how in silico clinical trials of cardiovascular disease are applied to specific cardiovascular diseases: carotid artery plaque modeling, aorta stenosis modeling, stent biodegradation modeling, surrogate AI model for left ventricle modeling, and more.This book is geared toward upper-level undergraduate and graduate students as well as for researchers in the domains of bioengineering, biomechanics, biomedical engineering and medicine.

This book covers in silico clinical trials of cardiovascular disease using a finite element and machine learning approach. Part I describes the fundamentals as well as the latest developments in the field: finite element modeling, system biology modeling for drug optimization, artificial intelligence approach for medical image processing, as well as pharmacokinetic and AI modeling. Part II provides use cases to describe how in silico clinical trials of cardiovascular disease are applied to specific cardiovascular diseases: carotid artery plaque modeling, aorta stenosis modeling, stent biodegradation modeling, surrogate AI model for left ventricle modeling, and more.This book is geared toward upper-level undergraduate and graduate students as well as for researchers in the domains of bioengineering, biomechanics, biomedical engineering and medicine.

The book Applied Artificial Intelligence 2: Medicine, Biology, Chemistry, Financial, Games, Engineering is providing exceptional chapters of the state-of-the-art research knowledge and results on the innovative theories, methodology and applications of artificial intelligence and its sub-domain like deep learning, machine learning in different areas such as medicine, economy, education, law, smart city, government, industry etc. Innovative research ideas on how to solve problems using artificial intelligence, both in R&D and real-time applications are presented. Chapters describe the advanced prototypes, systems, methodologies, tools and techniques and general survey papers, which indicate future directions. These Chapters are extended papers from the Second Serbian International Conference on Applied Artificial Intelligence (SICAAI), which was held in Kragujevac, Serbia, on May 19-20, 2023

This book aims at meeting the challenge of getting along with today’s unprecedented rate of innovation supported by disruptive digital technologies, which changed the perception of the productivity and effectiveness and opened a gateway to more than ever dynamic advances in solving the important societal challenges."Disruptive Information Technologies for a Smart Society" is the proceedings book of the 14th International Conference for Information Society and Technologies that brings together experts from various fields to discuss the latest advancements in industrial AI, digitalization in health, well-being and sport, enterprise information systems, large language models, and security and safety.The book and the conference serve as a platform for researchers of all career stages in technical sciences, especially Ph.D. students, practitioners, and industry experts in health care, AI and other areas to share and learn on the cutting-edge technologies and stay at the forefront of these rapidly evolving fields.

The book covers the state-of-the-art research knowledge and results on the innovative theories, methodology and applications of artificial intelligence and its sub-domain like deep learning in different areas such as medicine, economy, education, law, smart city, government, industry etc.

This book covers proceedings of the 15th International conference for information society and technologies that brings together experts from various fields to discuss the latest advancements in using AI and IoT to shape a future industry, digitalization of health, well-being and sport, energy and environment, generative AI, and large language models, machine learning, and software engineering. In recent years, disruptive digital technologies, such as AI and blockchain, changed the perception of productivity and effectiveness and opened a gateway to more than ever dynamic advances in solving the important societal challenges. Unprecedented level of scientific collaboration in those areas completely transformed the research landscape, through extensive flow of knowledge, information and data, making the research communities more digital than ever. Even beyond solving actual problems, disruptive tech contributed to creating new visionary objectives that could transform the way in which we live and work in the future information society. The book features a collection of papers that showcase novel approaches and practices in these areas, highlighting the potential of these technologies to disrupt traditional systems and pave the way for a smarter and more connected society.

This book bridges advanced mathematical foundations with real-world implementation, offering readers practical insight into deep learning architectures, reinforcement learning, predictive modeling, digital twins, and intelligent optimization systems. Artificial Intelligence is reshaping every major scientific and industrial domain. In this book, Nenad Filipovic presents a rigorous, interdisciplinary exploration of AI-driven solutions across medicine, biology, chemistry, finance, gaming systems, and engineering.From AI-enhanced diagnostics and computational physiology to molecular modeling, algorithmic trading, multi-agent systems, and smart manufacturing, the book demonstrates how intelligent algorithms transform complex data into actionable knowledge.Emphasizing transparency, robustness, and trustworthy AI principles, the book integrates statistical validation frameworks, computational algorithms, and applied case studies drawn from diverse high-impact fields.Designed for researchers, engineers, clinicians, financial analysts, and graduate students, this book provides a comprehensive roadmap for understanding and implementing AI in multidisciplinary environments. It stands as an essential reference for those seeking to harness artificial intelligence to solve real-world scientific and technological challenges