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This book provides a unique knowledge source of the FDA's regulatory processes to anyone interested in the development and approval of biomedical products.Navigating the FDA Regulatory Processes will be of particular importance for those innovating in biomedical devices, pharmacological therapies, and combination products, who are interested in considering regulatory affairs early on in product development. The authors offer a comprehensive exploration of FDA regulations, providing industry insights and guidance for navigating the complexities of drug and device development. The book offers concrete examples, industry perspectives, and historical context, ensuring clarity and aiding in successful understanding of the requirements for regulatory compliance. Readers will also gain a thorough understanding of FDA regulatory processes, from securing approvals to navigating expedited pathways. Lastly, the book provides unique insights into the FDA approach for emergency preparedness, including discussing the recent COVID-19 pandemic.Biomedical industry personnel, engineers, scientists, entrepreneurs, medical doctors, students, and anyone interested in the development and approval of medical products in the US will find this book useful and essential.

This book presents cutting-edge research and developments in the broad field of medical, biological engineering and computing. It gathers the second volume of the joint proceedings of the Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON) and the International Conference on Medical and Biological Engineering (CMBEBIH), which were held together on September 14-16, 2023, in Sarajevo, Bosnia and Herzegovina. Contributions report on innovative research and practices in molecular biology, tissue engineering and biotechnologies, covering not only medical but also industrial applications. Further, they describe advances in health technologies and medical devices, telemedicine, and robotic applications in clinical medicine and rehabilitation.

Engineered Biomaterials: Progress and Prospects presents state-of-the-art developments in the area of biomaterials research exemplified by experts in the fields of tissue engineering, wound healing, bio-diagnostics, novel therapeutics and advanced drug delivery systems.It provides a comprehensive account of preparation, characterisation, properties, processing, biological and clinical evaluation of a large variety of materials for specific biomedical applications. Basic concepts related to wound healing, tissue engineering and drug delivery systems, and the principal role played by macro, micro and nano scaled structures in biomaterials are presented in a clear manner. Developments in the area of conventional and advanced wound care strategies, materials for periodontal therapeutics, in-situ gelling tissue adhesives, biodegradable composites etc are illustrated in a lucid manner. Advanced processing techniques explored for the fabrication of micro-needles for vaccine delivery, 3D printing of personalized pharmaceuticals, bio-resorbable coatings, metallosurfactants and surface engineering of nanosystems are depicted in a straightforward and reasonable way.This book also discusses various advanced therapeutic and diagnostic systems such as magnetic nanoparticle based hyperthermia and their surface functionalization techniques. Lipid-based nano delivery systems for psoriasis, irritable bowel syndrome and pain management, polyrotaxane polymers, wearable devices for sensing etc are also depicted in this book. The contents are designed in a manner that will be highly suited for academic researchers, clinicians and industrialists who wish to explore in the versatile field of biomaterials as it contains a wealth of valuable information that will be equally useful to both beginners as well as established researchers.

Increase in consumer awareness of nutritional habits has placed automatic food analysis in the spotlight in recent years. However, food-logging is cumbersome and requires sufficient knowledge of the food item consumed. Additionally, keeping track of every meal can become a tedious task. Accurately documenting dietary caloric intake is crucial to manage weight loss, but also presents challenges because most of the current methods for dietary assessment must rely on memory to recall foods eaten. Food understanding from digital media has become a challenge with important applications in many different domains. Substantial research has demonstrated that digital imaging accurately estimates dietary intake in many environments and it has many advantages over other methods. However, how to derive the food information effectively and efficiently remains a challenging and open research problem. The provided recommendations could be based on calorie counting, healthy food and specific nutritional composition. In addition, if we also consider a system able to log the food consumed by every individual along time, it could provide health-related recommendations in the long-term. Computer Vision specialists have developed new methods for automatic food intake monitoring and food logging. Fourth Industrial Revolution [4.0 IR] technologies such as deep learning and computer vision robotics are key for sustainable food understanding. The need for AI based technologies that allow tracking of physical activities and nutrition habits are rapidly increasing and automatic analysis of food images plays an important role. Computer vision and image processing offers truly impressive advances to various applications like food analytics and healthcare analytics and can aid patients in keeping track of their calorie count easily by automating the calorie counting process. It can inform the user about the number of calories, proteins, carbohydrates, and other nutrients provided by each meal. The information is provided in real-time and thus proves to be an efficient method of nutrition tracking and can be shared with the dietician over the internet, reducing healthcare costs. This is possible by a system made up of, IoT sensors, Cloud-Fog based servers and mobile applications. These systems can generate data or images which can be analyzed using machine learning algorithms. Image Based Computing for Food and Health Analytics covers the current status of food image analysis and presents computer vision and image processing based solutions to enhance and improve the accuracy of current measurements of dietary intake. Many solutions are presented to improve the accuracy of assessment by analyzing health images, data and food industry based images captured by mobile devices. Key technique innovations based on Artificial Intelligence and deep learning-based food image recognition algorithms are also discussed. This book examines the usageof 4.0 industrial revolution technologies such as computer vision and artificial intelligence in the field of healthcare and food industry, providing a comprehensive understanding of computer vision and intelligence methodologies which tackles the main challenges of food and health processing. Additionally, the text focuses on the employing sustainable 4 IR technologies through which consumers can attain the necessary diet and nutrients and can actively monitor their health. In focusing specifically on the food industry and healthcare analytics, it serves as a single source for multidisciplinary information involving AI and vision techniques in the food and health sector. Current advances such as Industry 4.0 and Fog-Cloud based solutions are covered in full, offering readers a fully rounded view of these rapidly advancing health and food analysis systems.

The book contains peer-reviewed proceedings of the International Conference on Emergent Converging Technologies and Biomedical Systems 2021. It includes papers on wireless multimedia networks, green wireless networks, electric vehicles, biomedical signal processing and instrumentation, wearable sensors for health care monitoring, biomedical imaging, & bio-materials, modeling and simulation in medicine biomedical and health informatics. The book will serve as a useful guide for educators, researchers, and developers working in the area of signal processing, imaging, computing, instrumentation, artificial intelligence, and their related applications. This book will also provide support and aid to the researchers involved in designing the latest advancements in healthcare technologies.

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. The book covers the main approaches used in computational intelligence, including fuzzy logic, neural networks, evolutionary computation, learning theory, and probabilistic methods, all of which can be collectively viewed as soft computing. Other key approaches included are swarm intelligence and artificial immune systems. These approaches provide researchers with powerful tools for analysis and problem-solving when data is incomplete and when the problem under consideration is too complex for standard mathematics and the crisp logic approach of Boolean computing. - Provides an overview of the key methods of computational intelligence, including fuzzy logic, neural networks, evolutionary computation, learning theory, and probabilistic methods - Includes case studies and real-world examples of computational intelligence applied in a variety of research topics, including bioinformatics, biomedical engineering, big data analytics, information security, signal processing, machine learning, nanotechnology, and optimization techniques - Presents a thorough technical explanation on how computational intelligence is applied that is suitable for a wide range of multidisciplinary and interdisciplinary research

This book fosters a scientific debate for sophisticated approaches and cognitive technologies (such as deep learning, machine learning and advanced analytics) for enhanced healthcare services in light of the tremendous scope in the future of intelligent systems for healthcare. The authors discuss the proliferation of huge data sources (e.g. genomes, electronic health records (EHRs), mobile diagnostics, and wearable devices) and breakthroughs in artificial intelligence applications, which have unlocked the doors for diagnosing and treating multitudes of rare diseases. The contributors show how the widespread adoption of intelligent health based systems could help overcome challenges, such as shortages of staff and supplies, accessibility barriers, lack of awareness on certain health issues, identification of patient needs, and early detection and diagnosis of illnesses. This book is a small yet significant step towards exploring recent advances, disseminating state-of-the-art techniquesand deploying novel technologies in intelligent healthcare services and applications.Describes the advances of computing methodologies for life and medical science data;Presents applications of artificial intelligence in healthcare along with case studies and datasets;Provides an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.

This book presents the latest cutting edge research, theoretical methods, and novel applications in the field of computational intelligence and computational biological approaches that are aiming to combat COVID-19. The book gives the technological key drivers behind using AI to find drugs that target the virus, shedding light on the structure of COVID-19, detecting the outbreak and spread of new diseases, spotting signs of a COVID-19 infection in medical images, monitoring how the virus and lockdown is affecting mental health, and forecasting how COVID-19 cases and deaths will spread across cities and why. Further, the book helps readers understand computational intelligence techniques combating COVID-19 in a simple and systematic way.

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. - Provides a leading-edge survey of Data Science techniques and methods for research, mitigation and treatment of the COVID-19 virus - Integrates various Data Science techniques to provide a resource for COVID-19 researchers and clinicians around the world, including both positive and negative research findings - Provides insights into innovative data-oriented modeling and predictive techniques from COVID-19 researchers - Includes real-world feedback and user experiences from physicians and medical staff from around the world on the effectiveness of applied Data Science solutions