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Intelligent systems try to achieve, through the use of computers, flexible learning and adaptive activity like that found in the human brain. For the first time, this groundbreaking resource provides a detailed understanding of the analysis, design, and application of new intelligent systems in the biomedical industry.
Intelligent prediction and decision support systems are based on signal processing, computer vision (CV), machine learning (ML), software engineering (SE), knowledge based systems (KBS), data mining, artificial intelligence (AI) and include several systems developed from the study of expert systems (ES), genetic algorithms (GA), artificial neural networks (ANN) and fuzzy-logic systems The use of automatic decision support systems in design and manufacturing industry, healthcare and commercial software development systems has the following benifits: Cost savings in companies, due to employment of expert system technology. Fast decision making, completion of projects in time and development of new products. Improvement in decision making capability and quality. Usage of Knowledge database and Preservation of expertise of individuals Eases complex decision problems. Ex: Diagnosis in Healthcare To address the issues and challenges related to development, implementation and application of automatic and intelligent prediction and decision support systems in domains such as manufacturing, healthcare and software product design, development and optimization, this book aims to collect and publish wide ranges of quality articles such as original research contributions, methodological reviews, survey papers, case studies and/or reports covering intelligent systems, expert prediction systems, evaluation models, decision support systems and Computer Aided Diagnosis (CAD).
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 practical book is part of the new Artech House Methods in Bioengineering series - volumes designed to offer detailed guidance on authoritative methods for addressing specific bioengineering challenges. This volume is focused on the materials involved with nanoscale bioengineering. Nanomaterials are quickly moving into the mainstream as a critical component of biological research. Filling a critical gap in the current literature, this new resource presents practical, step-by-step methods to help professionals synthesize, characterize, functionalize and apply the nanomaterial that is most suitable for handling a given nanoscale bioengineering problem. Written and presented by the best scientists and engineers in their respective fields, the authors offer a clear and detailed understanding of how to carry out a wide range of important methods in this area.
Control Applications for Biomedical Engineering Systems presents different control engineering and modeling applications in the biomedical field. It is intended for senior undergraduate or graduate students in both control engineering and biomedical engineering programs. For control engineering students, it presents the application of various techniques already learned in theoretical lectures in the biomedical arena. For biomedical engineering students, it presents solutions to various problems in the field using methods commonly used by control engineers. Points out theoretical and practical issues to biomedical control systems Brings together solutions developed under different settings with specific attention to the validation of these tools in biomedical settings using real-life datasets and experiments Presents significant case studies on devices and applications
This volume presents the proceedings of the International Symposium on Biomedical Engineering and Medical Physics and is dedicated to the 150 anniversary of the Riga Technical University, Latvia. The content includes various hot topics in biomedical engineering and medical physics.
Intelligent systems, or artificial intelligence technologies, are playing an increasing role in areas ranging from medicine to the major manufacturing industries to financial markets. The consequences of flawed artificial intelligence systems are equally wide ranging and can be seen, for example, in the programmed trading-driven stock market crash of October 19, 1987. Intelligent Systems: Technology and Applications, Six Volume Set connects theory with proven practical applications to provide broad, multidisciplinary coverage in a single resource. In these volumes, international experts present case-study examples of successful practical techniques and solutions for diverse applications ranging from robotic systems to speech and signal processing, database management, and manufacturing.
This volume offers comprehensive coverage of intelligent systems, including fundamental aspects, software-, sensors-, and hardware-related issues. Moreover, the contributors to this volume provide, beyond a systematic overview of intelligent interfaces and systems, deep, practical knowledge in building and using intelligent systems in various applications. Special emphasis is placed on specific aspects and requirements in applications.
This textbook comprehensively covers the latest state-of-the-art methods and applications of artificial intelligence (AI) in medicine, placing these developments into a historical context. Factors that assist or hinder a particular technique to improve patient care from a cognitive informatics perspective are identified and relevant methods and clinical applications in areas including translational bioinformatics and precision medicine are discussed. This approach enables the reader to attain an accurate understanding of the strengths and limitations of these emerging technologies and how they relate to the approaches and systems that preceded them. With topics covered including knowledge-based systems, clinical cognition, machine learning and natural language processing, Intelligent Systems in Medicine and Health: The Role of AI details a range of the latest AI tools and technologies within medicine. Suggested additional readings and review questions reinforce the key points covered and ensure readers can further develop their knowledge. This makes it an indispensable resource for all those seeking up-to-date information on the topic of AI in medicine, and one that provides a sound basis for the development of graduate and undergraduate course materials.