Data Mining in Biomedicine Using Ontologies PDF Download
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Author: Mihail Popescu
Publisher: Artech House
ISBN: 1596933712
Category : Medical
Languages : en
Pages : 279
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Book Description
Presently, a growing number of ontologies are being built and used for annotating data in biomedical research. Thanks to the tremendous amount of data being generated, ontologies are now being used in numerous ways, including connecting different databases, refining search capabilities, interpreting experimental/clinical data, and inferring knowledge. This cutting-edge resource introduces you to latest developments in bio-ontologies. The book provides you with the theoretical foundations and examples of ontologies, as well as applications of ontologies in biomedicine, from molecular levels to clinical levels. You also find details on technological infrastructure for bio-ontologies. This comprehensive, one-stop volume presents a wide range of practical bio-ontology information, offering you detailed guidance in the clustering of biological data, protein classification, gene and pathway prediction, and text mining. More than 160 illustrations support key topics throughout the book.
Author: Mihail Popescu
Publisher: Artech House
ISBN: 1596933712
Category : Medical
Languages : en
Pages : 279
Get Book Here
Book Description
Presently, a growing number of ontologies are being built and used for annotating data in biomedical research. Thanks to the tremendous amount of data being generated, ontologies are now being used in numerous ways, including connecting different databases, refining search capabilities, interpreting experimental/clinical data, and inferring knowledge. This cutting-edge resource introduces you to latest developments in bio-ontologies. The book provides you with the theoretical foundations and examples of ontologies, as well as applications of ontologies in biomedicine, from molecular levels to clinical levels. You also find details on technological infrastructure for bio-ontologies. This comprehensive, one-stop volume presents a wide range of practical bio-ontology information, offering you detailed guidance in the clustering of biological data, protein classification, gene and pathway prediction, and text mining. More than 160 illustrations support key topics throughout the book.
Author: Mihail Popescu
Publisher:
ISBN: 9781596933712
Category :
Languages : en
Pages :
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Book Description
Author: Hsinchun Chen
Publisher: Springer Science & Business Media
ISBN: 038725739X
Category : Medical
Languages : en
Pages : 656
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Book Description
Comprehensively presents the foundations and leading application research in medical informatics/biomedicine. The concepts and techniques are illustrated with detailed case studies. Authors are widely recognized professors and researchers in Schools of Medicine and Information Systems from the University of Arizona, University of Washington, Columbia University, and Oregon Health & Science University. Related Springer title, Shortliffe: Medical Informatics, has sold over 8000 copies The title will be positioned at the upper division and graduate level Medical Informatics course and a reference work for practitioners in the field.
Author: Nigro, Hector Oscar
Publisher: IGI Global
ISBN: 1599046202
Category : Computers
Languages : en
Pages : 312
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Book Description
"Prior knowledge in data mining is helpful for selecting suitable data and mining techniques, pruning the space of hypothesis, representing the output in a comprehensible way, and improving the overall method. This book examines methodologies and research for the development of ontological foundations for data mining to enhance the ability of ontology utilization and design"--Provided by publisher.
Author: Sumeet Dua
Publisher: CRC Press
ISBN: 1439839395
Category : Computers
Languages : en
Pages : 434
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Book Description
This comprehensive volume demonstrates the broad scope of uses for data mining and includes detailed strategies and methodologies for analyzing data from biomedical images, signals, and systems. Written by experts in the field, it presents data mining techniques in the context of various important clinical issues, including diagnosis and grading of depression, identification and classification of arrhythmia and ischemia, and description of classification paradigms for mammograms. The book provides ample information and techniques to benefit researchers, practitioners, and educators of biomedical science and engineering.
Author: Panos M. Pardalos
Publisher: Springer Science & Business Media
ISBN: 038769319X
Category : Medical
Languages : en
Pages : 577
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Book Description
This volume presents an extensive collection of contributions covering aspects of the exciting and important research field of data mining techniques in biomedicine. Coverage includes new approaches for the analysis of biomedical data; applications of data mining techniques to real-life problems in medical practice; comprehensive reviews of recent trends in the field. The book addresses incorporation of data mining in fundamental areas of biomedical research: genomics, proteomics, protein characterization, and neuroscience.
Author: Andreas Holzinger
Publisher: Springer
ISBN: 3662439689
Category : Computers
Languages : en
Pages : 373
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Book Description
One of the grand challenges in our digital world are the large, complex and often weakly structured data sets, and massive amounts of unstructured information. This “big data” challenge is most evident in biomedical informatics: the trend towards precision medicine has resulted in an explosion in the amount of generated biomedical data sets. Despite the fact that human experts are very good at pattern recognition in dimensions of = 3; most of the data is high-dimensional, which makes manual analysis often impossible and neither the medical doctor nor the biomedical researcher can memorize all these facts. A synergistic combination of methodologies and approaches of two fields offer ideal conditions towards unraveling these problems: Human–Computer Interaction (HCI) and Knowledge Discovery/Data Mining (KDD), with the goal of supporting human capabilities with machine learning./ppThis state-of-the-art survey is an output of the HCI-KDD expert network and features 19 carefully selected and reviewed papers related to seven hot and promising research areas: Area 1: Data Integration, Data Pre-processing and Data Mapping; Area 2: Data Mining Algorithms; Area 3: Graph-based Data Mining; Area 4: Entropy-Based Data Mining; Area 5: Topological Data Mining; Area 6 Data Visualization and Area 7: Privacy, Data Protection, Safety and Security.
Author: Guo-Qiang Zhang
Publisher: Springer Nature
ISBN: 3031121317
Category : Computers
Languages : en
Pages : 258
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Book Description
The book synthesizes research on the analysis of biomedical ontologies using formal concept analysis, including through auditing, curation, and enhancement. As the evolution of biomedical ontologies almost inevitably involves manual work, formal methods are a particularly useful tool for ontological engineering and practice, particularly in uncovering unexpected "bugs" and content materials. The book first introduces simple but formalized strategies for discovering undesired and incoherent patterns in ontologies before exploring the application of formal concept analysis for semantic completeness. The book then turns to formal concept analysis, a classical approach used in the mathematical treatment of orders and lattices, as an ontological engineering principle, focusing on the structural property of ontologies with respect to its conformation to lattice or not (non-lattice). The book helpfully covers the development of more efficient algorithms for non-lattice detection and extraction required by exhaustive lattice/non-lattice analysis. The book goes on to highlight the power and utility of uncovering non-lattice structure for debugging ontologies and describes methods that leverage the linguistic information in concept names (labels) for ontological analysis. It also addresses visualization and performance evaluation issues before closing with an overview and forward-looking perspectives on the field. This book is intended for graduate students and researchers interested in biomedical ontologies and their applications. It can be a useful supplement for courses on knowledge representation and engineering and also provide readers with a reference for related scientific publications and literature to assist in identifying potential research topics. All mathematical concepts and notations used in this book can be found in standard discrete mathematics textbooks, and the appendix at the end of the book provides a list of key ontological resources, as well as annotated non-lattice and lattice examples that were discovered using the authors' methods, demonstrating how "bugs are fixed" by converting non-lattices to lattices with minimal edit changes.
Author: Sujata Dash
Publisher: John Wiley & Sons
ISBN: 1119711266
Category : Computers
Languages : en
Pages : 450
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Book Description
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.
Author: Albert Burger
Publisher: Springer Science & Business Media
ISBN: 1846288851
Category : Technology & Engineering
Languages : en
Pages : 356
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Book Description
This book provides a timely and first-of-its-kind collection of papers on anatomy ontologies. It is interdisciplinary in its approach, bringing together the relevant expertise from computing and biomedical studies. The book aims to provide readers with a comprehensive understanding of the foundations of anatomical ontologies and the-state-of-the-art in terms of existing tools and applications. It also highlights challenges that remain today.
