information discovery on electronic health records chapman hall crc data mining and knowledge discovery series

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Information Discovery On Electronic Health Records

Author : Vagelis Hristidis
ISBN : 1420090410
Genre : Medical
File Size : 47. 51 MB
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Exploiting the rich information found in electronic health records (EHRs) can facilitate better medical research and improve the quality of medical practice. Until now, a trivial amount of research has been published on the challenges of leveraging this information. Addressing these challenges, Information Discovery on Electronic Health Records explores the technology to unleash the data stored in EHRs. Assembling a truly interdisciplinary team of experts, the book tackles medical privacy concerns, the lack of standardization for the representation of EHRs, missing or incorrect values, and the availability of multiple rich health ontologies. It looks at how to search the EHR collection given a user query and return relevant fragments from the EHRs. It also explains how to mine the EHR collection to extract interesting patterns, group entities to various classes, or decide whether an EHR satisfies a given property. Most of the book focuses on textual or numeric data of EHRs, where more searching and mining progress has occurred. A chapter on the processing of medical images is also included. Maintaining a uniform style across chapters and minimizing technical jargon, this book presents the various ways to extract useful knowledge from EHRs. It skillfully discusses how EHR data can be effectively searched and mined.

Privacy Aware Knowledge Discovery

Author : Francesco Bonchi
ISBN : 9781439803660
Genre : Computers
File Size : 69. 79 MB
Format : PDF
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Covering research at the frontier of this field, Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques presents state-of-the-art privacy-preserving data mining techniques for application domains, such as medicine and social networks, that face the increasing heterogeneity and complexity of new forms of data. Renowned authorities from prominent organizations not only cover well-established results—they also explore complex domains where privacy issues are generally clear and well defined, but the solutions are still preliminary and in continuous development. Divided into seven parts, the book provides in-depth coverage of the most novel reference scenarios for privacy-preserving techniques. The first part gives general techniques that can be applied to various applications discussed in the rest of the book. The second section focuses on the sanitization of network traces and privacy in data stream mining. After the third part on privacy in spatio-temporal data mining and mobility data analysis, the book examines time series analysis in the fourth section, explaining how a perturbation method and a segment-based method can tackle privacy issues of time series data. The fifth section on biomedical data addresses genomic data as well as the problem of privacy-aware information sharing of health data. In the sixth section on web applications, the book deals with query log mining and web recommender systems. The final part on social networks analyzes privacy issues related to the management of social network data under different perspectives. While several new results have recently occurred in the privacy, database, and data mining research communities, a uniform presentation of up-to-date techniques and applications is lacking. Filling this void, Privacy-Aware Knowledge Discovery presents novel algorithms, patterns, and models, along with a significant collection of open problems for future investigation.

Machine Learning And Knowledge Discovery For Engineering Systems Health Management

Author : Ashok N. Srivastava
ISBN : 9781439841792
Genre : Computers
File Size : 23. 15 MB
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Machine Learning and Knowledge Discovery for Engineering Systems Health Management presents state-of-the-art tools and techniques for automatically detecting, diagnosing, and predicting the effects of adverse events in an engineered system. With contributions from many top authorities on the subject, this volume is the first to bring together the two areas of machine learning and systems health management. Divided into three parts, the book explains how the fundamental algorithms and methods of both physics-based and data-driven approaches effectively address systems health management. The first part of the text describes data-driven methods for anomaly detection, diagnosis, and prognosis of massive data streams and associated performance metrics. It also illustrates the analysis of text reports using novel machine learning approaches that help detect and discriminate between failure modes. The second part focuses on physics-based methods for diagnostics and prognostics, exploring how these methods adapt to observed data. It covers physics-based, data-driven, and hybrid approaches to studying damage propagation and prognostics in composite materials and solid rocket motors. The third part discusses the use of machine learning and physics-based approaches in distributed data centers, aircraft engines, and embedded real-time software systems. Reflecting the interdisciplinary nature of the field, this book shows how various machine learning and knowledge discovery techniques are used in the analysis of complex engineering systems. It emphasizes the importance of these techniques in managing the intricate interactions within and between the systems to maintain a high degree of reliability.

Temporal Data Mining

Author : Theophano Mitsa
ISBN : 1420089773
Genre : Computers
File Size : 32. 19 MB
Format : PDF, ePub
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Temporal data mining deals with the harvesting of useful information from temporal data. New initiatives in health care and business organizations have increased the importance of temporal information in data today. From basic data mining concepts to state-of-the-art advances, Temporal Data Mining covers the theory of this subject as well as its application in a variety of fields. It discusses the incorporation of temporality in databases as well as temporal data representation, similarity computation, data classification, clustering, pattern discovery, and prediction. The book also explores the use of temporal data mining in medicine and biomedical informatics, business and industrial applications, web usage mining, and spatiotemporal data mining. Along with various state-of-the-art algorithms, each chapter includes detailed references and short descriptions of relevant algorithms and techniques described in other references. In the appendices, the author explains how data mining fits the overall goal of an organization and how these data can be interpreted for the purpose of characterizing a population. She also provides programs written in the Java language that implement some of the algorithms presented in the first chapter. Check out the author's blog at http://theophanomitsa.wordpress.com/

Next Generation Of Data Mining

Author : Hillol Kargupta
ISBN : 1420085875
Genre : Computers
File Size : 57. 62 MB
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Drawn from the US National Science Foundation’s Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation (NGDM 07), Next Generation of Data Mining explores emerging technologies and applications in data mining as well as potential challenges faced by the field. Gathering perspectives from top experts across different disciplines, the book debates upcoming challenges and outlines computational methods. The contributors look at how ecology, astronomy, social science, medicine, finance, and more can benefit from the next generation of data mining techniques. They examine the algorithms, middleware, infrastructure, and privacy policies associated with ubiquitous, distributed, and high performance data mining. They also discuss the impact of new technologies, such as the semantic web, on data mining and provide recommendations for privacy-preserving mechanisms. The dramatic increase in the availability of massive, complex data from various sources is creating computing, storage, communication, and human-computer interaction challenges for data mining. Providing a framework to better understand these fundamental issues, this volume surveys promising approaches to data mining problems that span an array of disciplines.

Books In Print

Author :
ISBN : UOM:39015045491084
Genre : American literature
File Size : 83. 45 MB
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Books in print is the major source of information on books currently published and in print in the United States. The database provides the record of forthcoming books, books in-print, and books out-of-print.

Subject Guide To Books In Print

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ISBN : STANFORD:36105025888533
Genre : American literature
File Size : 28. 5 MB
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Forthcoming Books

Author : Rose Arny
ISBN : UOM:39015046868983
Genre : American literature
File Size : 84. 51 MB
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