Nanotechnology in Conservative Dentistry provides a detailed review of the use of nanotechnology in conservative dentistry, from diagnosis and restorative materials, through to tissue engineering and regeneration. This book covers fundamental topics in the field of conservative dentistry, including caries therapy, dentin reconstruction, pulp protection and more; each chapter reviews and discusses how nanotechnology can be implemented as a novel approach to traditional conservative dentistry techniques, exploring the many uses and advantages of this fast-growing technology. Various nanobiomaterials and technologies are covered, as well as assessment of the biocompatibility and toxicological risks of utilizing nanotechnology in dentistry. Nanotechnology in Conservative Dentistry will help dentists and materials science academics alike, understand the potential of nanotechnology in dentistry, building on and going beyond traditional concepts and techniques in this field.

Tailor-Made and Functionalized Biopolymer Systems: For Drug Delivery and Biomedical Applications covers the design and application of these functionalized and tailor-made biopolymers and biopolymer systems intended for drug delivery and biomedical applications. Various concepts, design protocols and biomedical applications of tailor-made biopolymer systems are covered, guiding the reader from theoretical knowledge to practical application. Authored by an array of experts from global institutions, this book offers an interdisciplinary approach to how tailor-made biopolymers lead to novel drug delivery and treatment solutions. This will be a useful reference to a broad audience, including biomedical engineers, materials scientists, pharmacologists and chemists.

Leveraging Artificial Intelligence in Global Epidemics provides readers with a detailed technical description of the role Artificial Intelligence plays in various stages of a disease outbreak, using COVID-19 as a case study. In the fight against epidemics, medical staff are on the front line; but behind the lines the battle is fought by researchers, and data scientists. Artificial Intelligence has been helping researchers with computer modeling and simulation for predictions about disease progression, the overall economic situation, tax incomes and population development. In the same manner, AI can prepare researchers for any emergency situation by backing the medical science. Artificial Intelligence plays a key and cutting-edge role in the preparedness for and dealing with the outbreak of global epidemics. It can help researchers analyze global data about known viruses to predict the patterns of the next pandemic and the impacts it will have. Not only prediction, AI plays an increasingly important role in assessing readiness, early detection, identification of patients, generating recommendations, situation awareness and more. It is up to the right input and the innovative ways by humans to leverage what AI can do. As COVID-19 has grabbed the world and its economy today, an analysis of the COVID-19 outbreak and the global responses and analytics will pay a long way in preparing humanity for such future situations.

Bioinspired and Biomimetic Materials for Drug Delivery delves into the potential of bioinspired materials in drug delivery, detailing each material type and its latest developments. In the last decade, biomimetic and bioinspired materials and technology has garnered increased attention in drug delivery research. Various material types including polymer, small molecular, protein, peptide, cholesterol, polysaccharide, nano-crystal and hybrid materials are widely considered in drug delivery research. However, biomimetic and bioinspired materials and technology have shown promising results for use in therapeutics, due to their high biocompatibility and reduced immunogenicity. Such materials include dopamine, extracellular exosome, bile acids, ionic liquids, and red blood cell. This book covers each of these materials in detail, reviewing their potential and usage in drug delivery. As such, this book will be a great source of information for biomaterials scientists, biomedical engineers and those working in pharmaceutical research.

Generative Adversarial Networks (GAN) have started a revolution in Deep Learning, and today GAN is one of the most researched topics in Artificial Intelligence. Generative Adversarial Networks for Image-to-Image Translation provides a comprehensive overview of the GAN (Generative Adversarial Network) concept starting from the original GAN network to various GAN-based systems such as Deep Convolutional GANs (DCGANs), Conditional GANs (cGANs), StackGAN, Wasserstein GANs (WGAN), cyclical GANs, and many more. The book also provides readers with detailed real-world applications and common projects built using the GAN system with respective Python code. A typical GAN system consists of two neural networks, i.e., generator and discriminator. Both of these networks contest with each other, similar to game theory. The generator is responsible for generating quality images that should resemble ground truth, and the discriminator is accountable for identifying whether the generated image is a real image or a fake image generated by the generator. Being one of the unsupervised learning-based architectures, GAN is a preferred method in cases where labeled data is not available. GAN can generate high-quality images, images of human faces developed from several sketches, convert images from one domain to another, enhance images, combine an image with the style of another image, change the appearance of a human face image to show the effects in the progression of aging, generate images from text, and many more applications. GAN is helpful in generating output very close to the output generated by humans in a fraction of second, and it can efficiently produce high-quality music, speech, and images.

Real-Time Data Acquisition in Human Physiology: Real-Time Acquisition, Processing, and Interpretation-A MATLAB-Based Approach focuses on the design and development of a computer-based system to detect and digitally process human ECG, EMG, and carotid pulse waveforms in real time. The indigenous system developed and described in this book allows for an easy-to-interface, simple hardware arrangement for bio-signal detection. The computational functionality of MATLAB is verified for viewing, digital filtration, and feature extraction of acquired bio-signals. This book demonstrates a method of providing a relatively cost-effective solution to human physiology real-time monitoring, processing, and interpretation that is more realizable and would directly benefit a larger population of patients.

State of the Art in Neural Networks and Their Applications presents the latest advances in artificial neural networks and their applications across a wide range of clinical diagnoses. Advances in the role of machine learning, artificial intelligence, deep learning, cognitive image processing and suitable data analytics useful for clinical diagnosis and research applications are covered, including relevant case studies. The application of Neural Network, Artificial Intelligence, and Machine Learning methods in biomedical image analysis have resulted in the development of computer-aided diagnostic (CAD) systems that aim towards the automatic early detection of several severe diseases. State of the Art in Neural Networks and Their Applications is presented in two volumes. Volume 1 covers the state-of-the-art deep learning approaches for the detection of renal, retinal, breast, skin, and dental abnormalities and more.

Micro and Nano Systems for Biophysical Studies of Cells and Small Organisms provides a comprehensive introduction to the state-of-the-art micro and nano systems that have recently been developed and applied to biophysical studies of cells and small organisms. These micro and nano systems span from microelectromechanical systems (MEMS) and microfluidic devices to robotic micro-nanomanipulation systems. These biophysical studies range from cell mechanics to the neural science of worms and Drosophila. This book will help readers understand the fundamentals surrounding the development of these tools and teach them the most recent advances in cellular and organismal biophysics enabled by these technologies.

Neural Engineering for Autism Spectrum Disorder, Volume One: Imaging and Signal Analysis Techniques presents the latest advances in neural engineering and biomedical engineering as applied to the clinical diagnosis and treatment of Autism Spectrum Disorder (ASD). Advances in the role of neuroimaging, infrared spectroscopy, sMRI, fMRI, DTI, social behaviors and suitable data analytics useful for clinical diagnosis and research applications for Autism Spectrum Disorder are covered, including relevant case studies. The application of brain signal evaluation, EEG analytics, feature selection, and analysis of blood oxygen level-dependent (BOLD) signals are presented for detection and estimation of the degree of ASD.

Bionanocomposites in Tissue Engineering and Regenerative Medicine explores novel uses of these in tissue engineering and regenerative medicine. This book offers an interdisplinary approach, combining chemical, biomedical engineering, materials science and pharmacological aspects of the characterization, synthesis and application of bionanocomposites. Chapters cover a broad selection of bionanocomposites including chitosan, alginate and more, which are utilized in tissue engineering, wound healing, bone repair, drug formulation, cancer therapy, drug delivery, cartilage regeneration and dental implants. Additional sections of Bionanocomposites in Tissue Engineering and Regenerative Medicine discuss, in detail, the safety aspects and circular economy of bionanocomposites - offering an insight into the commercial and industrial aspects of these important materials. Bionanocomposites in Tissue Engineering and Regenerative Medicine will prove a highly useful text for for those in the fields of biomedical engineering, chemistry, pharmaceutics and materials science, both in academia and industrial R&D groups.

The third edition of Joint Replacement Technology provides a thoroughly updated review of recent developments in joint replacement technology. Joint replacement is a standard treatment for joint degradation and has improved the quality of life of millions of patients. Collaboration between clinicians and researchers is critical to its continued success and to meet the rising expectations of patients and surgeons. This edition covers a range of updated and new content, ranging from chapters on materials analysis and selection, to methodologies and techniques used for joint replacement and clinical challenges of replacing specific joints. Key topics include tribological considerations and experiments; challenges in joint bearing surfaces; cementless fixation techniques; healing responses to implants. Clinical challenges and perspectives are covered with the aid of case studies. Thanks to its widespread collaboration and international contributors, Joint Replacement Technology, Third Edition is useful for materials scientists and engineers in both academia and the biomedical industry. Chemists, clinicians, and other researchers in this area will also find this text invaluable.

Microfluidic Devices for Biomedical Applications, Second Edition provides updated coverage on the fundamentals of microfluidics, while also exploring a wide range of medical applications. Chapters review materials and methods, microfluidic actuation mechanisms, recent research on droplet microfluidics, applications in drug discovery and controlled-delivery, including micro needles, consider applications of microfluidic devices in cellular analysis and manipulation, tissue engineering and their role in developing tissue scaffolds, and cover the applications of microfluidic devices in diagnostic sensing, including genetic analysis, low-cost bioassays, viral detection, and radio chemical synthesis. This book is an essential reference for medical device manufacturers, scientists and researchers concerned with microfluidics in the field of biomedical applications and life-science industries.

Advances in Cancer Biomarkers Research provides a thorough and detailed description of cancer biomarkers for diagnostic, prognostic and therapeutics in several cancer types. The book presents a compendium of topics related to current advanced research, along with fundamental knowledge that will help readers fully comprehend the field of cancer biomarkers. Topics discussed include such the role of genetic mechanisms, epigenetics, DNA and microRNA in different cancers, signaling pathways and exosomes. In addition, the book discusses biomarker research applied to several cancer types, such as head and neck, urological, lung, bone tumors, hematological and neurological malignancies and breast cancers.This will be a valuable resource for cancer researchers, oncologists, graduate students and members of the biomedical field who are interested in the potential of biomarkers in cancer research and treatment.

Autonomous Robot-Aided Optical Manipulation for Biological Cells gives a systematically and almost self-contained description of the many facets of modeling, sensing, and control techniques or experimentally exploring emerging trends in optical manipulation of biological cell in micro/nanorobotics systems. To achieve biomedical applications, reliability design, modeling, and precision control are vitally important for the development of engineering systems. With the advances in modeling, sensing, and control techniques, it is opportunistic to exploit them for the benefit of reliability design, actuation, and precision control of micro/nanomanipulation systems to expanding the applications of robot at the micro and nano scales, especially in biomedical engineering. This book presents new techniques in reliability modeling and advanced control of robot-aided optical manipulation of biological cells systems. The book will be beneficial to the researchers within robotics, mechatronics, biomedical engineering, and automatic control society, including both academic and industrial parts.

Biomedical Applications of Electrospinning and Electrospraying describes the principles and laboratory set up for electrospinning and electrospraying, addressing a range of biomedical applications. Sections cover novel combinational approaches, such as electrospinning/spraying and 3D printing. Electrospinning has evolved from being a technique to prepare random networks of textile fibers to a technique to fabricate highly ordered patterns of biomedical materials of defined scale. The technological advancements in recent years with regard to the way the jet is facilitated, how the jet path is controlled, and how the fibers are collected have provided invaluable insights into controlled fabrication of a material of choice. Additionally, the electrospray technique has also evolved from being a technique to prepare food formulations to a technique to prepare cell encapsulated beads for transplantation in clinics. Several innovations in this line, such as those leading to core-shell materials have tremendously changed the way the technique is used. Thus, a combinational approach using electrospinning, electrospraying and 3D printing has emerged.

Principles and Labs for Deep Learning provides the knowledge and techniques needed to help readers design and develop deep learning models. Deep Learning techniques are introduced through theory, comprehensively illustrated, explained through the TensorFlow source code examples, and analyzed through the visualization of results. The structured methods and labs provided by Dr. Huang and Dr. Le enable readers to become proficient in TensorFlow to build deep Convolutional Neural Networks (CNNs) through custom APIs, high-level Keras APIs, Keras Applications, and TensorFlow Hub. Each chapter has one corresponding Lab with step-by-step instruction to help the reader practice and accomplish a specific learning outcome. Deep Learning has been successfully applied in diverse fields such as computer vision, audio processing, robotics, natural language processing, bioinformatics and chemistry. Because of the huge scope of knowledge in Deep Learning, a lot of time is required to understand and deploy useful, working applications, hence the importance of this new resource. Both theory lessons and experiments are included in each chapter to introduce the techniques and provide source code examples to practice using them. All Labs for this book are placed on GitHub to facilitate the download. The book is written based on the assumption that the reader knows basic Python for programming and basic Machine Learning.

Lignin-based Materials for Biomedical Applications: Preparation, Characterization, and Implementation explores the emerging area of lignin-based materials as a platform for advanced biomedical applications, guiding the reader from source through to implementation. The first part of the book introduces the basics of lignin, including extraction methods, chemical modifications, structure and composition, and properties that make lignin suitable for biomedical applications. In addition, structural characterization techniques are described in detail. The next chapters focus on the preparation of lignin-based materials for biomedical applications, presenting methodologies for lignin-based nanoparticles, hydrogels, aerogels, and nanofibers, and providing in-depth coverage of lignin-based materials with specific properties-including antioxidant properties, UV absorbing capability, antimicrobial properties, and colloidal particles with tailored properties-and applications, such as drug and gene delivery, and tissue engineering. Finally, future perspectives and possible new applications are considered. This is an essential reference for all those with an interest in lignin-based materials and their biomedical applications, including researchers and advanced students across bio-based polymers, polymer science, polymer chemistry, biomaterials, nanotechnology, materials science and engineering, drug delivery, and biomedical engineering, as well as industrial R&D and scientists involved with bio-based polymers, specifically for biomedical applications.

Digital Health: Exploring Use and Integration of Wearables is the first book to show how and why engineering theory is used to solve real-world clinical applications, considering the knowledge and lessons gathered during many international projects. This book provides a pragmatic A to Z guide on the design, deployment and use of wearable technologies for laboratory and remote patient assessment, aligning the shared interests of diverse professions to meet with a common goal of translating engineering theory to modern clinical practice. It offers multidisciplinary experiences to guide engineers where no clinically advice and expertise may be available. Entering the domain of wearables in healthcare is notoriously difficult as projects and ideas often fail to deliver due to the lack of clinical understanding, i.e., what do healthcare professionals and patients really need? This book provides engineers and computer scientists with the clinical guidance to ensure their novel work successfully translates to inform real-world clinical diagnosis, treatment and management.

Data Science for COVID-19 presents leading-edge research on data science techniques for the detection, mitigation, treatment and elimination of COVID-19. Sections provide an introduction to data science for COVID-19 research, considering past and future pandemics, as well as related Coronavirus variations. Other chapters cover a wide range of Data Science applications concerning COVID-19 research, including Image Analysis and Data Processing, Geoprocessing and tracking, Predictive Systems, Design Cognition, mobile technology, and telemedicine solutions. The book then covers Artificial Intelligence-based solutions, innovative treatment methods, and public safety. Finally, readers will learn about applications of Big Data and new data models for mitigation.

Information Physics: Physics-Information and Quantum Analogies for Complex Modeling presents a new theory of complex systems that uses analogy across various aspects of physics, including electronics, magnetic circuits and quantum mechanics. The book explains the quantum approach to system theory that can be understood as an extension of classical system models. The main idea is that in many complex systems there are incomplete pieces of overlapping information that must be strung together to find the most consistent model. This incomplete information can be understood as a set of non-exclusive observer results. Because they are non-exclusive, each observer registers different pictures of reality.

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians.

Biomedical Engineering Tools for Management of Patients with COVID-19 presents biomedical engineering tools under research (and in development) that can be used for the management of COVID-19 patients, along with BME tools in the global environment that curtail and prevent the spread of the virus. BME tools covered in the book include new disinfectants and sterilization equipment, testing devices for rapid and accurate COVID-19 diagnosis, Internet of Things applications in COVID-19 hospitals, analytics, Data Science and statistical modeling applied to COVID-19 tracking, Smart City instruments and applications, and more. Later sections discuss smart tools in telemedicine and e-health. Biomedical engineering tools can provide engineers, computer scientists, clinicians and other policymakers with solutions for managing patient treatment, applying data analysis techniques, and applying tools to help the general population curtail spread of the virus.

Thermal Ablation Therapy: Theory and Simulation includes detailed theoretical and technical concepts of thermal ablation therapy in different body organs. Concepts of ablation technology based on different thermal ablation methods are introduced, along with changes in the tissues' mechanical properties due to thermal denaturation. The book emphasizes the mathematical and engineering concepts of RF and MW energy propagation through tissues and where high heating rates produced by MW systems can overcome the heat-sink effects from nearby vessels. The design and tuning of the MW antennas to deliver energy efficiently to specific organ systems such as the liver or lung is also covered. Other sections cover the computational modeling of radiofrequency ablation and microwave ablation procedures for developing and implementing new efficient ablation in clinical systems, numerical simulations for different scenarios of different organs with different size using RF and MW ablation systems with different antennas'/probes design and configurations, and numerical techniques for temperature profile in tissues.

Foundational Handbook of Artificial Intelligence in Healthcare and Bioscience: A User Friendly Guide for IT Professionals, Healthcare Providers, Researchers, and Clinicians uses color-coded illustrations to explain AI from its basics to modern technologies. Other sections cover extensive, current literature research and citations regarding AI's role in the business and clinical aspects of health care. The book provides readers with a unique opportunity to appreciate AI technology in practical terms, understand its applications, and realize its profound influence on the clinical and business aspects of health care. Artificial Intelligence is a disruptive technology that is having a profound and growing influence on the business of health care as well as medical diagnosis, treatment, research and clinical delivery. The AI relationships in health care are complex, but understandable, especially when discussed and developed from their foundational elements through to their practical applications in health care.

Cell Instructive Materials to Control and Guide Cell Function: Programmable Bioactive Interfaces looks at the key determinants of the dynamic interface between cell and materials and how this can be applied in developing new, bioactive biomaterials surfaces. The interface between cell and synthetic materials has attracted considerable scientific and technological interest, leading to the awareness that functional interfaces can actively guide and control specific adhesion and recognitions events.