Biomedical Data And Applications
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Handbook Of Data Science Approaches For Biomedical Engineering
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Author : Valentina Emilia Balas
language : en
Publisher: Academic Press
Release Date : 2019-11-13
Handbook Of Data Science Approaches For Biomedical Engineering written by Valentina Emilia Balas and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-13 with Science categories.
Handbook of Data Science Approaches for Biomedical Engineering covers the research issues and concepts of biomedical engineering progress and the ways they are aligning with the latest technologies in IoT and big data. In addition, the book includes various real-time/offline medical applications that directly or indirectly rely on medical and information technology. Case studies in the field of medical science, i.e., biomedical engineering, computer science, information security, and interdisciplinary tools, along with modern tools and the technologies used are also included to enhance understanding. Today, the role of Big Data and IoT proves that ninety percent of data currently available has been generated in the last couple of years, with rapid increases happening every day. The reason for this growth is increasing in communication through electronic devices, sensors, web logs, global positioning system (GPS) data, mobile data, IoT, etc. - Provides in-depth information about Biomedical Engineering with Big Data and Internet of Things - Includes technical approaches for solving real-time healthcare problems and practical solutions through case studies in Big Data and Internet of Things - Discusses big data applications for healthcare management, such as predictive analytics and forecasting, big data integration for medical data, algorithms and techniques to speed up the analysis of big medical data, and more
Biomedical Data And Applications
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Author : Amandeep S. Sidhu
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-06-16
Biomedical Data And Applications written by Amandeep S. Sidhu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-16 with Computers categories.
Compared with data from general application domains, modern biological data has many unique characteristics. The goal of this book is to cover data and applications identifying new issues and directions for future research in biomedical domain.
Introduction To Biomedical Data Science
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Author : Robert Hoyt
language : en
Publisher: Lulu.com
Release Date : 2019-11-24
Introduction To Biomedical Data Science written by Robert Hoyt and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-24 with Science categories.
Overview of biomedical data science -- Spreadsheet tools and tips -- Biostatistics primer -- Data visualization -- Introduction to databases -- Big data -- Bioinformatics and precision medicine -- Programming languages for data analysis -- Machine learning -- Artificial intelligence -- Biomedical data science resources -- Appendix A: Glossary -- Appendix B: Using data.world -- Appendix C: Chapter exercises.
Biomedical Informatics
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Author : Edward H. Shortliffe
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-02
Biomedical Informatics written by Edward H. Shortliffe and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-02 with Medical categories.
The practice of modern medicine and biomedical research requires sophisticated information technologies with which to manage patient information, plan diagnostic procedures, interpret laboratory results, and carry out investigations. Biomedical Informatics provides both a conceptual framework and a practical inspiration for this swiftly emerging scientific discipline at the intersection of computer science, decision science, information science, cognitive science, and biomedicine. Now revised and in its third edition, this text meets the growing demand by practitioners, researchers, and students for a comprehensive introduction to key topics in the field. Authored by leaders in medical informatics and extensively tested in their courses, the chapters in this volume constitute an effective textbook for students of medical informatics and its areas of application. The book is also a useful reference work for individual readers needing to understand the role that computers can play in the provision of clinical services and the pursuit of biological questions. The volume is organized so as first to explain basic concepts and then to illustrate them with specific systems and technologies.
Biomedical Data Mining For Information Retrieval
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Author : Sujata Dash
language : en
Publisher: John Wiley & Sons
Release Date : 2021-08-24
Biomedical Data Mining For Information Retrieval written by Sujata Dash and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-24 with Computers categories.
BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.
Biomedical Data Visualization Methods And Applications
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Author : Guangchuang Yu
language : en
Publisher: Frontiers Media SA
Release Date : 2022-05-24
Biomedical Data Visualization Methods And Applications written by Guangchuang Yu and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-24 with Science categories.
Strategies In Biomedical Data Science
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Author : Jay A. Etchings
language : en
Publisher: John Wiley & Sons
Release Date : 2017-01-03
Strategies In Biomedical Data Science written by Jay A. Etchings and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-03 with Medical categories.
An essential guide to healthcare data problems, sources, and solutions Strategies in Biomedical Data Science provides medical professionals with much-needed guidance toward managing the increasing deluge of healthcare data. Beginning with a look at our current top-down methodologies, this book demonstrates the ways in which both technological development and more effective use of current resources can better serve both patient and payer. The discussion explores the aggregation of disparate data sources, current analytics and toolsets, the growing necessity of smart bioinformatics, and more as data science and biomedical science grow increasingly intertwined. You'll dig into the unknown challenges that come along with every advance, and explore the ways in which healthcare data management and technology will inform medicine, politics, and research in the not-so-distant future. Real-world use cases and clear examples are featured throughout, and coverage of data sources, problems, and potential mitigations provides necessary insight for forward-looking healthcare professionals. Big Data has been a topic of discussion for some time, with much attention focused on problems and management issues surrounding truly staggering amounts of data. This book offers a lifeline through the tsunami of healthcare data, to help the medical community turn their data management problem into a solution. Consider the data challenges personalized medicine entails Explore the available advanced analytic resources and tools Learn how bioinformatics as a service is quickly becoming reality Examine the future of IOT and the deluge of personal device data The sheer amount of healthcare data being generated will only increase as both biomedical research and clinical practice trend toward individualized, patient-specific care. Strategies in Biomedical Data Science provides expert insight into the kind of robust data management that is becoming increasingly critical as healthcare evolves.
Predictive Modeling In Biomedical Data Mining And Analysis
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Author : Sudipta Roy
language : en
Publisher: Academic Press
Release Date : 2022-08-28
Predictive Modeling In Biomedical Data Mining And Analysis written by Sudipta Roy and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-28 with Science categories.
Predictive Modeling in Biomedical Data Mining and Analysis presents major technical advancements and research findings in the field of machine learning in biomedical image and data analysis. The book examines recent technologies and studies in preclinical and clinical practice in computational intelligence. The authors present leading-edge research in the science of processing, analyzing and utilizing all aspects of advanced computational machine learning in biomedical image and data analysis. As the application of machine learning is spreading to a variety of biomedical problems, including automatic image segmentation, image classification, disease classification, fundamental biological processes, and treatments, this is an ideal reference. Machine Learning techniques are used as predictive models for many types of applications, including biomedical applications. These techniques have shown impressive results across a variety of domains in biomedical engineering research. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood, hence the need for new resources and information. - Includes predictive modeling algorithms for both Supervised Learning and Unsupervised Learning for medical diagnosis, data summarization and pattern identification - Offers complete coverage of predictive modeling in biomedical applications, including data visualization, information retrieval, data mining, image pre-processing and segmentation, mathematical models and deep neural networks - Provides readers with leading-edge coverage of biomedical data processing, including high dimension data, data reduction, clinical decision-making, deep machine learning in large data sets, multimodal, multi-task, and transfer learning, as well as machine learning with Internet of Biomedical Things applications
Emerging Trends And Applications Of Deep Learning For Biomedical Data Analysis
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Author : Smita Sharma
language : en
Publisher: Elsevier
Release Date : 2025-05-02
Emerging Trends And Applications Of Deep Learning For Biomedical Data Analysis written by Smita Sharma and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-02 with Science categories.
Emerging Trends and Applications of Deep Learning for Biomedical Data Analysis introduces the latest emerging trends and applications of deep learning in biomedical data analysis. This book delves into various use cases where deep learning is applied in industrial, social, and personal contexts within the biomedical domain. By gaining a comprehensive understanding of deep learning in biomedical data analysis, readers will develop the skills to critically evaluate research papers, methodologies, and emerging trends. In 11 chapters, this book provides insights into the fundamentals of the latest research trends in the applications of deep learning in biosciences. With several case studies and use cases, it familiarizes the reader with a comprehensive understanding of deep learning algorithms, architectures, and methodologies speci cally applicable to biomedical data analysis. This title is an ideal reference for researchers across the biomedical sciences.● Provides a succinct overview of the cutting-edge technologies that are altering disease diagnosis, patient monitoring, and medical research● Bridges the gap between biomedical engineering and deep learning by providing a comprehensive resource for comprehending the intersection of these disciplines● Investigates how deep learning may change healthcare by providing new insights, diagnostics, and treatments via intelligent biomedical systems
Data Analytics In Biomedical Engineering And Healthcare
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Author : Kun Chang Lee
language : en
Publisher: Academic Press
Release Date : 2020-10-18
Data Analytics In Biomedical Engineering And Healthcare written by Kun Chang Lee and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-18 with Science categories.
Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning in health sciences and biomedical data. The book is useful for those working with big data analytics in biomedical research, medical industries, and medical research scientists. The book covers health analytics, data science, and machine and deep learning applications for biomedical data, covering areas such as predictive health analysis, electronic health records, medical image analysis, computational drug discovery, and genome structure prediction using predictive modeling. Case studies demonstrate big data applications in healthcare using the MapReduce and Hadoop frameworks. - Examines the development and application of data analytics applications in biomedical data - Presents innovative classification and regression models for predicting various diseases - Discusses genome structure prediction using predictive modeling - Shows readers how to develop clinical decision support systems - Shows researchers and specialists how to use hybrid learning for better medical diagnosis, including case studies of healthcare applications using the MapReduce and Hadoop frameworks