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Motivated by the explosion of molecular data on humans-particularly data associated with individual patients-and the sense that there are large, as-yet-untapped opportunities to use this data to improve health outcomes, Toward Precision Medicine explores the feasibility and need for "a new taxonomy of human disease based on molecular biology" and develops a potential framework for creating one. The book says that a new data network that integrates emerging research on the molecular makeup of diseases with clinical data on individual patients could drive the development of a more accurate classification of diseases and ultimately enhance diagnosis and treatment. The "new taxonomy" that emerges would define diseases by their underlying molecular causes and other factors in addition to their traditional physical signs and symptoms. The book adds that the new data network could also improve biomedical research by enabling scientists to access patients' information during treatment while still protecting their rights. This would allow the marriage of molecular research and clinical data at the point of care, as opposed to research information continuing to reside primarily in academia. Toward Precision Medicine notes that moving toward individualized medicine requires that researchers and health care providers have access to very large sets of health- and disease-related data linked to individual patients. These data are also critical for developing the information commons, the knowledge network of disease, and ultimately the new taxonomy.
A complete set of best practices, tools, and techniques for turning conversations into a rich source of business information Many organizations are now recognizing that the untapped knowledge of their members can be used to benefit every aspect of their business, from making smarter and faster decisions to improving products and efficiency. This book offers a clear-cut road map for building a successful knowledge management system to capture and fully exploit the knowledge exchanged in conversations. Written by two of the foremost experts in online communities, this book covers a set of best practices, tools, and techniques for using conversation and online interaction to provide affordable and effective knowledge-based benefits and solutions. With a unique and invaluable perspective, the authors offer guidance for collecting, capturing, and cataloging knowledge so that it can be used to improve efficiency and reduce costs in areas ranging from internal procedures through customer relations and product development. This book provides step-by-step solutions for developing an effective knowledge network, including how to: * Formulate strategies and create action plans * Select the right tools for peer-to-peer networks, interactive communities, and events * Work with legacy systems * Train staff and stimulate participation * Improve productivity and measurement criteria The companion Web site contains templates, checklists, a discussion board, and links to software.
How does a telecommunications company function when its right hand often doesn't know what its left hand is doing? How do rapidly expanding, interdisciplinary organizations hold together and perform their knowledge work? In this book, Clay Spinuzzi draws on two warring theories of work activity - activity theory and actor-network theory - to examine the networks of activity that make a telecommunications company work and thrive. In doing so, Spinuzzi calls a truce between the two theories, bringing them to the negotiating table to parley about work. Specifically, about net work: the coordinative work that connects, coordinates, and stabilizes polycontextual work activities. To develop this uneasy dialogue, Spinuzzi examines the texts, trades, and technologies at play at Telecorp, both historically and empirically. Drawing on both theories, Spinuzzi provides new insights into how net work actually works and how our theories and research methods can be extended to better understand it.
Principles of Semantic Networks: Explorations in the Representation of Knowledge provides information pertinent to the theory and applications of semantic networks. This book deals with issues in knowledge representation, which discusses theoretical topics independent of particular implementations. Organized into three parts encompassing 19 chapters, this book begins with an overview of semantic network structure for representing knowledge as a pattern of interconnected nodes and arcs. This text then analyzes the concepts of subsumption and taxonomy and synthesizes a framework that integrates many previous approaches and goes beyond them to provide an account of abstract and partially defines concepts. Other chapters consider formal analyses, which treat the methods of reasoning with semantic networks and their computational complexity. This book discusses as well encoding linguistic knowledge. The final chapter deals with a formal approach to knowledge representation that builds on ideas originating outside the artificial intelligence literature in research on foundations for programming languages. This book is a valuable resource for mathematicians.
Introducing the basic concepts in total program control of the intelligent agents and machines, Intelligent Internet Knowledge Networks explores the design and architecture of information systems that include and emphasize the interactive role of modern computer/communication systems and human beings. Here, you’ll discover specific network configurations that sense environments, presented through case studies of IT platforms, electrical governments, medical networks, and educational networks.
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
This book outlines how network technology can support, foster and enhance the Knowledge Management, Sharing and Development (KMSD) processes in professional environments through the activation of both formal and informal knowledge flows. Understanding how ICT can be made available to such flows in the knowledge society is a factor that cannot be disregarded and is confirmed by the increasing interest of companies in new forms of software-mediated social interaction. The latter factor is in relation both to the possibility of accelerating internal communication and problem solving processes, and/or in relation to dynamics of endogenous knowledge growth of human resources.The book will focus specifically on knowledge flow (KF) processes occurring within networked communities of professionals (NCP) and the associated virtual community environments (VCE) that foster horizontal dynamics in the management, sharing and development of fresh knowledge. Along this line a further key issue will concern the analysis and evaluation techniques of the impact of Network Technology use on both community KF and NCP performance. - The proposal of a taxonomy of Network Technology uses to support formal and informal knowledge flows - Analyses how Web 2.0 and Web 3.0 technology is deeply modifying the dynamics connected to KF and KM - Discusses dynamics underlying horizontal KF sharing processes within NCP
Software development continues to be an ever-evolving field as organizations require new and innovative programs that can be implemented to make processes more efficient, productive, and cost-effective. Agile practices particularly have shown great benefits for improving the effectiveness of software development and its maintenance due to their ability to adapt to change. It is integral to remain up to date with the most emerging tactics and techniques involved in the development of new and innovative software. The Research Anthology on Agile Software, Software Development, and Testing is a comprehensive resource on the emerging trends of software development and testing. This text discusses the newest developments in agile software and its usage spanning multiple industries. Featuring a collection of insights from diverse authors, this research anthology offers international perspectives on agile software. Covering topics such as global software engineering, knowledge management, and product development, this comprehensive resource is valuable to software developers, software engineers, computer engineers, IT directors, students, managers, faculty, researchers, and academicians.
Why does so much of our society look as it did in the past? Our schools,our government, our religious organizations, our media - while more complex, have maintained their general structure and shape. Classroomstructure today, with the exception of a computer or an LCD projector, looks remarkably unchanged: teacher at the front, students i n rows. Our business processes are still built on theories and viewpoints that existed over a century ago (with periodic amendments from thinkers like Drucker 2). In essence, we have transferred (not transformed) our physical identity to online spaces and structures.