Biomedical engineering

Biomedical optical imaging is a rapidly emerging research area with widespread fundamental research and clinical applications.

Receptors: Models for Binding, Trafficking, and Signaling bridges the gap between chemical engineering and cell biology by lucidly and practically demonstrating how a mathematical modeling approach combined with quantitative experiments can provide enhanced understanding of cell phenomena involving receptor/ligand interactions.

Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models focuses on the relationship between three different multidisciplinary branches of engineering: Biomedical Engineering, Cognitive Science and Computer Science through Artificial Intelligence models.

Advanced Rehabilitative Technology: Neural Interfaces and Devices teaches readers how to acquire and process bio-signals using biosensors and acquisition devices, how to identify the human movement intention and decode the brain signal, how to design physiological and musculoskeletal models and establish the neural interfaces, and how to develop neural devices and control them efficiently using biological signals.

Electronic Assistive Technology (EAT) is a subset of a wider range of products and services known as Assistive Technology (AT).

The Routledge Handbook of the Ethics of Human Enhancement provides readers with a philosophically rich and scientifically grounded analysis of human enhancement and its ethical implications.

MATLAB Programming for Biomedical Engineers and Scientists provides an easy-to-learn introduction to the fundamentals of computer programming in MATLAB.

Wound Healing Biomaterials: Volume One, Therapies and Regeneration discusses the types of wounds associated with trauma, illness, or surgery that can sometimes be extremely complex and difficult to heal.

Intelligent machines are populating our social, economic and political spaces.

Stimuli Responsive Polymeric Nanocarriers for Drug Delivery Applications: Volume Two: Advanced Nanocarriers for Therapeutics discusses, in detail, the recent trends in designing dual and multi-responsive polymers and nanoparticles for safe drug delivery.

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There have been tremendous strides in cellular transplantation in recent years, leading to accepted practice for the treatment of certain diseases, and use for many others in trial phases.

Neural Engineering for Autism Spectrum Disorder, Volume Two: Diagnosis and Clinical Analysis presents the latest advances in neural engineering and biomedical engineering as applied to the clinical diagnosis and treatment of Autism Spectrum Disorder (ASD).

ODE/PDE Analysis of Antibiotic/Antimicrobial Resistance: Programming in R presents mathematical models for antibiotic/antimicrobial resistance based on ordinary and partial differential equations (ODE/PDEs).

Applications of Computational Intelligence in Multi-Disciplinary Research provides the readers with a comprehensive handbook for applying the powerful principles, concepts, and algorithms of computational intelligence to a wide spectrum of research cases.

Deep Learning for Medical Applications with Unique Data informs readers about the most recent deep learning-based medical applications in which only unique data gathered in real cases are used.

Wearable Technology in Medicine and Health Care provides readers with the most current research and information on the clinical and biomedical applications of wearable technology.

3D Bioprinting and Nanotechnology in Tissue Engineering and Regenerative Medicine, Second Edition provides an in-depth introduction to bioprinting and nanotechnology and their industrial applications.

Data Science for COVID-19 presents leading-edge research on data science techniques for the detection, mitigation, treatment and elimination of COVID-19.

Security and Privacy Issues in Internet of Medical Things addresses the security challenges faced by healthcare providers and patients.

Artificial Intelligence and Machine Learning for Predictive and Analytical Rendering in Edge Computing focuses on the role of AI and machine learning as it impacts and works alongside Edge Computing.

Deep Learning in Bioinformatics: Techniques and Applications in Practice introduces the topic in an easy-to-understand way, exploring how it can be utilized for addressing important problems in bioinformatics, including drug discovery, de novo molecular design, sequence analysis, protein structure prediction, gene expression regulation, protein classification, biomedical image processing and diagnosis, biomolecule interaction prediction, and in systems biology.

Multi-Objective Combinatorial Optimization Problems and Solution Methods discusses the results of a recent multi-objective combinatorial optimization achievement that considered metaheuristic, mathematical programming, heuristic, hyper heuristic and hybrid approaches.

Big Data permeates all aspects of modern life, and while there is no shortage of potential benefits resulting from this, author Henrik Skaug Saetra argues that we must also understand the threats Big Data poses to liberty.

In the age of data science, the rapidly increasing amount of data is a major concern in numerous applications of computing operations and data storage.

Storing Digital Binary Data into Cellular DNA demonstrates how current digital information storage systems have short longevity and limited capacity, also pointing out that their production and consumption of data exceeds supply.

Perinatal Stem Cells provides researchers and clinicians with a comprehensive description of the current clinical and pre-clinical applications of stem cells derived from perinatal sources, such as amniotic fluid, placenta and placental membranes, the umbilical cord and Wharton's jelly.

Microfluidic Devices for Biomedical Applications, Second Edition provides updated coverage on the fundamentals of microfluidics, while also exploring a wide range of medical applications.

Deep learning, a branch of Artificial Intelligence and machine learning, has led to new approaches to solving problems in a variety of domains including data science, data analytics and biomedical engineering.

Web Semantics strengthen the description of web resources to exploit them better and make them more meaningful for both humans and machines, thereby contributing to the development of a knowledgeintensive data web.

Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications.

Porous Silicon for Biomedical Applications, Second Edition, provides an updated guide to the diverse range of biomedical applications of porous silicon, from biosensing and imaging to tissue engineering and cancer therapy.

Thermal Ablation Therapy: Theory and Simulation includes detailed theoretical and technical concepts of thermal ablation therapy in different body organs.

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).

Deep Learning (DL) is a method of machine learning, running over Artificial Neural Networks, that uses multiple layers to extract high-level features from large amounts of raw data.

Nuclear Medicine and Molecular Imaging offers complete coverage of this exciting and key area of biomedicine, seamlessly fusing the science behind nuclear medicine with the clinical aspects of diagnostic imaging.

The Handbook of Immunological Properties of Engineered Nanomaterials provides a comprehensive overview of the current literature, methodologies, and translational and regulatory considerations in the field of nanoimmunotoxicology.

Generative Adversarial Networks (GAN) have started a revolution in Deep Learning, and today GAN is one of the most researched topics in Artificial Intelligence.

Nanorobotics and Nanodiagnostics in Integrative Biology and Biomedicine "e;Nanorobotics and nanodiagnostics"e; can be defined as a new generation of biohybrid and nanorobotics that translate fundamental biological principles into engineering design rules, or integrative living components into synthetic structures to create biorobots and nanodiagnotics that perform like natural systems.

Security in IoT Social Networks takes a deep dive into security threats and risks, focusing on real-world social and financial effects.

Current Research in Neuroadaptive Technology provides readers with insight into the state-of-the-art field of neuroadaptive technology.

Now in its fifth edition, Principles of Tissue Engineering has been the definite resource in the field of tissue engineering for more than a decade.

State of the Art on Grammatical Inference Using Evolutionary Method presents an approach for grammatical inference (GI) using evolutionary algorithms.

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.

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare.

Nature-Inspired Optimization Algorithms, Second Edition provides an introduction to all major nature-inspired algorithms for optimization.

This book takes the notions of adaptivity and learning from the realm of engineering into the realm of biology and natural processes.

**Selected for Doody's Core Titles(R) 2024 in Endocrinology/Metabolic Disease**Updated with new and expanded chapters, Endocrine Disruption and Human Health, Second Edition provides an introduction to what endocrine disruptors are, the issues surrounding them, the source of these chemicals in the ecosystem and the mechanisms of action and assay systems.

Handbook of Computational Intelligence in Biomedical Engineering and Healthcare helps readers analyze and conduct advanced research in specialty healthcare applications surrounding oncology, genomics and genetic data, ontologies construction, bio-memetic systems, biomedical electronics, protein structure prediction, and biomedical data analysis.

Handbook of Decision Support Systems for Neurological Disorders provides readers with complete coverage of advanced computer-aided diagnosis systems for neurological disorders.