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Applications of Computational Tools in Biosciences and Medical Engineering

Applications of Computational Tools in Biosciences and Medical Engineering
Author: Andreas Öchsner
Publisher: Springer
Total Pages: 217
Release: 2015-06-09
Genre: Technology & Engineering
ISBN: 3319194704
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This monograph presents the latest developments and applications of computational tools related to the biosciences and medical engineering. Computational tools such as the finite element methods, computer-aided design and optimization as well as visualization techniques such as computed axial tomography open completely new research fields with a closer joining of the engineering and bio/medical area. Nevertheless, there are still hurdles since both directions are based on quite different ways of education. Often even the “language” is sometimes different from discipline to discipline. This monograph reports the results of different multi-disciplinary research projects, for example, from the areas of scaffolds and synthetic bones, implants and medical devices and medical materials. It is also shown that the application of computational methods often necessitates mathematical and experimental methods.

Advanced Computational Approaches to Biomedical Engineering

Advanced Computational Approaches to Biomedical Engineering
Author: Punam K. Saha
Publisher: Springer Science & Business Media
Total Pages: 224
Release: 2014-01-23
Genre: Computers
ISBN: 3642415393
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There has been rapid growth in biomedical engineering in recent decades, given advancements in medical imaging and physiological modelling and sensing systems, coupled with immense growth in computational and network technology, analytic approaches, visualization and virtual-reality, man-machine interaction and automation. Biomedical engineering involves applying engineering principles to the medical and biological sciences and it comprises several topics including biomedicine, medical imaging, physiological modelling and sensing, instrumentation, real-time systems, automation and control, signal processing, image reconstruction, processing and analysis, pattern recognition, and biomechanics. It holds great promise for the diagnosis and treatment of complex medical conditions, in particular, as we can now target direct clinical applications, research and development in biomedical engineering is helping us to develop innovative implants and prosthetics, create new medical imaging technologies and improve tools and techniques for the detection, prevention and treatment of diseases. The contributing authors in this edited book present representative surveys of advances in their respective fields, focusing in particular on techniques for the analysis of complex biomedical data. The book will be a useful reference for graduate students, researchers and industrial practitioners in computer science, biomedical engineering, and computational and molecular biology.

Biocomputation and Biomedical Informatics: Case Studies and Applications

Biocomputation and Biomedical Informatics: Case Studies and Applications
Author: Lazakidou, Athina A.
Publisher: IGI Global
Total Pages: 356
Release: 2009-11-30
Genre: Computers
ISBN: 1605667692
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"This book provides a compendium of terms, definitions, and explanations of concepts, processes, and acronyms"--Provided by publisher.

Advances in Computational and Bio-Engineering

Advances in Computational and Bio-Engineering
Author: S. Jyothi
Publisher: Springer Nature
Total Pages: 650
Release: 2020-07-19
Genre: Mathematics
ISBN: 3030469395
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This book gathers state-of-the-art research in computational engineering and bioengineering to facilitate knowledge exchange between various scientific communities. Computational engineering (CE) is a relatively new discipline that addresses the development and application of computational models and simulations often coupled with high-performance computing to solve complex physical problems arising in engineering analysis and design in the context of natural phenomena. Bioengineering (BE) is an important aspect of computational biology, which aims to develop and use efficient algorithms, data structures, and visualization and communication tools to model biological systems. Today, engineering approaches are essential for biologists, enabling them to analyse complex physiological processes, as well as for the pharmaceutical industry to support drug discovery and development programmes.

Computational Approaches in Biotechnology and Bioinformatics

Computational Approaches in Biotechnology and Bioinformatics
Author: Pranav Deepak Pathak
Publisher: CRC Press
Total Pages: 404
Release: 2024-05-27
Genre: Technology & Engineering
ISBN: 1040008801
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Volume 1 of Computational Approaches in Bioengineering—Computational Approaches in Biotechnology and Bioinformatics—explores many significant topics of biomedical engineering and bioinformatics in an easily understandable format. It explores recent developments and applications in bioinformatics, biomechanics, artificial intelligence (AI), signal processing, wearable sensors, biomaterials, cell biology, synthetic biology, biostatistics, prosthetics, big data, and algorithms. From applications of biomaterials in advanced drug delivery systems to the role of big data, AI, and machine learning in disease diagnosis and treatment, the book will help readers understand how these technologies are being applied across the areas of biomedical engineering, bioinformatics, and healthcare. The chapters also include case studies on the role of medical robots in surgery and the determination of protein structure using genetic algorithms. The contributors are all leading experts across multiple disciplines and provide chapters that truly represent a complete view of these state-of-the-art technologies. FEATURES Covers a wide range of subjects from biomedical engineering like wearable devices, biomaterials, synthetic biology, phytochemical extraction, and prosthetics Explores AI, machine learning, big data analysis, and algorithms in biomedical engineering and bioinformatics in an easily understandable format Includes case studies on the role of medical robots in surgery and the determination of protein structure using genetic algorithms Discusses genetic diagnosis, classification, and risk prediction in cancer using next-generation sequencing in oncology This book is ideally designed for biomedical professionals, biomedical engineers, healthcare professionals, data engineers, clinicians, physicians, medical students, hospital directors, clinical researchers, and others who work in the field of artificial intelligence, bioinformatics, and computational biology.

Advances in Computational and Bio-Engineering

Advances in Computational and Bio-Engineering
Author: S. Jyothi
Publisher: Springer Nature
Total Pages: 488
Release: 2020-07-06
Genre: Mathematics
ISBN: 3030469433
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This book gathers state-of-the-art research in computational engineering and bioengineering to facilitate knowledge exchange between various scientific communities. Computational engineering (CE) is a relatively new discipline that addresses the development and application of computational models and simulations often coupled with high-performance computing to solve complex physical problems arising in engineering analysis and design in the context of natural phenomena. Bioengineering (BE) is an important aspect of computational biology, which aims to develop and use efficient algorithms, data structures, and visualization and communication tools to model biological systems. Today, engineering approaches are essential for biologists, enabling them to analyse complex physiological processes, as well as for the pharmaceutical industry to support drug discovery and development programmes.

Advances in Computational Biology

Advances in Computational Biology
Author: Hamid R. Arabnia
Publisher: Springer Science & Business Media
Total Pages: 732
Release: 2010-09-24
Genre: Science
ISBN: 1441959130
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Proceedings of The 2009 International Conference on Bioinformatics and Computational Biology in Las Vegas, NV, July 13-16, 2009. Recent advances in Computational Biology are covered through a variety of topics. Both inward research (core areas of computational biology and computer science) and outward research (multi-disciplinary, Inter-disciplinary, and applications) will be covered during the conferences. These include: Gene regulation, Gene expression databases, Gene pattern discovery and identification, Genetic network modeling and inference, Gene expression analysis, RNA and DNA structure and sequencing, Biomedical engineering, Microarrays, Molecular sequence and structure databases, Molecular dynamics and simulation, Molecular sequence classification, alignment and assembly, Image processing In medicine and biological sciences, Sequence analysis and alignment, Informatics and Statistics in Biopharmaceutical Research, Software tools for computational biology and bioinformatics, Comparative genomics; and more.

Translational Bioinformatics Applications in Healthcare

Translational Bioinformatics Applications in Healthcare
Author: Khalid Raza
Publisher: CRC Press
Total Pages: 211
Release: 2021-04-20
Genre: Technology & Engineering
ISBN: 1000375234
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Translational bioinformatics (TBI) involves development of storage, analytics, and advanced computational methods to harvest knowledge from voluminous biomedical and genomic data into 4P healthcare (proactive, predictive, preventive, and participatory). Translational Bioinformatics Applications in Healthcare offers a detailed overview on concepts of TBI, biological and clinical databases, clinical informatics, and pertinent real-case applications. It further illustrates recent advancements, tools, techniques, and applications of TBI in healthcare, including Internet of Things (IoT) potential, toxin databases, medical image analysis and telemedicine applications, analytics of COVID-19 CT images, viroinformatics and viral diseases, and COVID-19–related research. Covers recent technologies such as Blockchain, IoT, and Big data analytics in bioinformatics Presents the role of translational bioinformatic methods in the field of viroinformatics, as well as in drug development and repurposing Includes translational healthcare and NGS for clinical applications Illustrates translational medicine systems and their applications in better healthcare Explores medical image analysis with focus on CT images and novel coronavirus disease detection Aimed at researchers and graduate students in computational biology, data mining and knowledge discovery, algorithms and complexity, and interdisciplinary fields of studies, including bioinformatics, health-informatics, biostatistics, biomedical engineering, and viroinformatics. Khalid Raza is an Assistant Professor, the Department of Computer Science, Jamia Millia Islamia (Central University), New Delhi. His research interests include translational bioinformatics, computational intelligence methods and its applications in bioinformatics, viroinformatics, and health informatics. Nilanjan Dey is an Associate Professor, the Department of Computer Science and Engineering, JIS University, Kolkata, India. His research interests include medical imaging, machine learning, computer-aided diagnosis, and data mining.

Scalable Pattern Recognition Algorithms

Scalable Pattern Recognition Algorithms
Author: Pradipta Maji
Publisher: Springer Science & Business Media
Total Pages: 316
Release: 2014-03-19
Genre: Computers
ISBN: 3319056301
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This book addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models. The text reviews both established and cutting-edge research, providing a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics. Features: integrates different soft computing and machine learning methodologies with pattern recognition tasks; discusses in detail the integration of different techniques for handling uncertainties in decision-making and efficiently mining large biological datasets; presents a particular emphasis on real-life applications, such as microarray expression datasets and magnetic resonance images; includes numerous examples and experimental results to support the theoretical concepts described; concludes each chapter with directions for future research and a comprehensive bibliography.

Computational and Analytic Methods in Biological Sciences

Computational and Analytic Methods in Biological Sciences
Author: Akshara Makrariya
Publisher: CRC Press
Total Pages: 325
Release: 2023-05-31
Genre: Computers
ISBN: 1000879879
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Despite major advances in healthcare over the past century, the successful treatment of cancer has remained a significant challenge, and cancers are the second leading cause of death worldwide behind cardiovascular disease. Early detection and survival are important issues to control cancer. The development of quantitative methods and computer technology has facilitated the formation of new models in medical and biological sciences. The application of mathematical modelling in solving many real-world problems in medicine and biology has yielded fruitful results. In spite of advancements in instrumentations technology and biomedical equipment, it is not always possible to perform experiments in medicine and biology for various reasons. Thus, mathematical modelling and simulation are viewed as viable alternatives in such situations, and are discussed in this book. The conventional diagnostic techniques of cancer are not always effective as they rely on the physical and morphological appearance of the tumour. Early stage prediction and diagnosis is very difficult with conventional techniques. It is well known that cancers are involved in genome level changes. As of now, the prognosis of various types of cancer depends upon findings related to the data generated through different experiments. Several machine learning techniques exist in analysing the data of expressed genes; however, the recent results related with deep learning algorithms are more accurate and accommodative, as they are effective in selecting and classifying informative genes. This book explores the probabilistic computational deep learning model for cancer classification and prediction.