Interactive Knowledge Discovery and Data Mining in Biomedical Informatics

Interactive Knowledge Discovery and Data Mining in Biomedical Informatics

Author: Andreas Holzinger

Publisher: Springer

Published: 2014-06-17

Total Pages: 373

ISBN-13: 3662439689

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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.


Patents in the Knowledge-Based Economy

Patents in the Knowledge-Based Economy

Author: National Research Council

Publisher: National Academies Press

Published: 2003-08-11

Total Pages: 352

ISBN-13: 0309167183

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This volume assembles papers commissioned by the National Research Council's Board on Science, Technology, and Economic Policy (STEP) to inform judgments about the significant institutional and policy changes in the patent system made over the past two decades. The chapters fall into three areas. The first four chapters consider the determinants and effects of changes in patent "quality." Quality refers to whether patents issued by the U.S. Patent and Trademark Office (USPTO) meet the statutory standards of patentability, including novelty, nonobviousness, and utility. The fifth and sixth chapters consider the growth in patent litigation, which may itself be a function of changes in the quality of contested patents. The final three chapters explore controversies associated with the extension of patents into new domains of technology, including biomedicine, software, and business methods.


Planning for Long-Term Use of Biomedical Data

Planning for Long-Term Use of Biomedical Data

Author: National Academies of Sciences, Engineering, and Medicine

Publisher: National Academies Press

Published: 2020-07-09

Total Pages: 93

ISBN-13: 0309672759

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Biomedical research data sets are becoming larger and more complex, and computing capabilities are expanding to enable transformative scientific results. The National Institutes of Health's (NIH's) National Library of Medicine (NLM) has the unique role of ensuring that biomedical research data are findable, accessible, interoperable, and reusable in an ethical manner. Tools that forecast the costs of long-term data preservation could be useful as the cost to curate and manage these data in meaningful ways continues to increase, as could stewardship to assess and maintain data that have future value. The National Academies of Sciences, Engineering, and Medicine convened a workshop on July 11-12, 2019 to gather insight and information in order to develop and demonstrate a framework for forecasting long-term costs for preserving, archiving, and accessing biomedical data. Presenters and attendees discussed tools and practices that NLM could use to help researchers and funders better integrate risk management practices and considerations into data preservation, archiving, and accessing decisions; methods to encourage NIH-funded researchers to consider, update, and track lifetime data; and burdens on the academic researchers and industry staff to implement these tools, methods, and practices. This publication summarizes the presentations and discussion of the workshop.


Enhancing Scientific Reproducibility in Biomedical Research Through Transparent Reporting

Enhancing Scientific Reproducibility in Biomedical Research Through Transparent Reporting

Author: National Academies of Sciences, Engineering, and Medicine

Publisher: National Academies Press

Published: 2020-05-28

Total Pages: 143

ISBN-13: 0309663490

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Sharing knowledge is what drives scientific progress - each new advance or innovation in biomedical research builds on previous observations. However, for experimental findings to be broadly accepted as credible by the scientific community, they must be verified by other researchers. An essential step is for researchers to report their findings in a manner that is understandable to others in the scientific community and provide sufficient information for others to validate the original results and build on them. In recent years, concern has been growing over a number of studies that have failed to replicate previous results and evidence from larger meta-analyses, which have pointed to the lack of reproducibility in biomedical research. On September 25 and 26, 2019, the National Academies of Science, Engineering, and Medicine hosted a public workshop in Washington, DC, to discuss the current state of transparency in the reporting of preclinical biomedical research and to explore opportunities for harmonizing reporting guidelines across journals and funding agencies. Convened jointly by the Forum on Drug Discovery, Development, and Translation; the Forum on Neuroscience and Nervous System Disorders; the National Cancer Policy Forum; and the Roundtable on Genomics and Precision Health, the workshop primarily focused on transparent reporting in preclinical research, but also considered lessons learned and best practices from clinical research reporting. This publication summarizes the presentation and discussion of the workshop.


Sourcebook of Models for Biomedical Research

Sourcebook of Models for Biomedical Research

Author: P. Michael Conn

Publisher: Springer Science & Business Media

Published: 2008-03-07

Total Pages: 756

ISBN-13: 1597452858

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The collection of systems represented in this volume is a unique effort to reflect the diversity and utility of models used in biomedicine. That utility is based on the consideration that observations made in particular organisms will provide insight into the workings of other, more complex systems. This volume is therefore a comprehensive and extensive collection of these important medical parallels.


Collaborative Computational Technologies for Biomedical Research

Collaborative Computational Technologies for Biomedical Research

Author: Sean Ekins

Publisher: John Wiley & Sons

Published: 2011-08-04

Total Pages: 462

ISBN-13: 1118026020

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Methods, Processes, and Tools for Collaboration "The time has come to fundamentally rethink how we handle the building of knowledge in biomedical sciences today. This book describes how the computational sciences have transformed into being a key knowledge broker, able to integrate and operate across divergent data types." Bryn Williams-Jones, Associate Research Fellow, Pfizer The pharmaceutical industry utilizes an extended network of partner organizations in order to discover and develop new drugs, however there is currently little guidance for managing information and resources across collaborations. Featuring contributions from the leading experts in a range of industries, Collaborative Computational Technologies for Biomedical Research provides information that will help organizations make critical decisions about managing partnerships, including: Serving as a user manual for collaborations Tackling real problems from both human collaborative and data and informatics perspectives Providing case histories of biomedical collaborations and technology-specific chapters that balance technological depth with accessibility for the non-specialist reader A must-read for anyone working in the pharmaceuticals industry or academia, this book marks a major step towards widespread collaboration facilitated by computational technologies.


Open Source Software in Life Science Research

Open Source Software in Life Science Research

Author: Lee Harland

Publisher: Elsevier

Published: 2012-10-31

Total Pages: 583

ISBN-13: 1908818247

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The free/open source approach has grown from a minor activity to become a significant producer of robust, task-orientated software for a wide variety of situations and applications. To life science informatics groups, these systems present an appealing proposition - high quality software at a very attractive price. Open source software in life science research considers how industry and applied research groups have embraced these resources, discussing practical implementations that address real-world business problems.The book is divided into four parts. Part one looks at laboratory data management and chemical informatics, covering software such as Bioclipse, OpenTox, ImageJ and KNIME. In part two, the focus turns to genomics and bioinformatics tools, with chapters examining GenomicsTools and EBI Atlas software, as well as the practicalities of setting up an 'omics' platform and managing large volumes of data. Chapters in part three examine information and knowledge management, covering a range of topics including software for web-based collaboration, open source search and visualisation technologies for scientific business applications, and specific software such as DesignTracker and Utopia Documents. Part four looks at semantic technologies such as Semantic MediaWiki, TripleMap and Chem2Bio2RDF, before part five examines clinical analytics, and validation and regulatory compliance of free/open source software. Finally, the book concludes by looking at future perspectives and the economics and free/open source software in industry. - Discusses a broad range of applications from a variety of sectors - Provides a unique perspective on work normally performed behind closed doors - Highlights the criteria used to compare and assess different approaches to solving problems