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Medical knowledge extraction from big data, Koutsojannis, Constantinos M.


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Автор: Koutsojannis, Constantinos M.
Название:  Medical knowledge extraction from big data
ISBN: 9781536179255
Издательство: Nova Science
Классификация:

ISBN-10: 1536179256
Обложка/Формат: Hardback
Страницы: 247
Вес: 0.47 кг.
Дата издания: 30.07.2020
Язык: English
Размер: 157 x 231 x 21
Читательская аудитория: Professional & vocational
Ключевые слова: Data mining
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Поставляется из: Англии
Описание: Data mining refers to the activity of going through big data sets to look for relevant information. As human health care data are the most difficult of all data to collect and their primary direction is the treatment of patients, and secondarily dealing with research, almost the only vindication for collecting medical data is to benefit the disease. All data miners should take into account that Medical Knowledge Extraction is internally connected with the Evidence-Based Medical approach because it uses data for already treated or not patients and there are times that opposites to Guideline Based medical practice. Additonally all researchers should be aware when are dealing with medical databases they may face the possibility that their work will never be accepted or even used from health care professionals if all these obligations will not be correctly addressed from the early beginning. In the present book, one can find after the three introductory chapters, a number of successfully evaluated applications that have been developed after mining approaches in Big or smaller amount (according to the application) of medical Data in different fields of every day clinical practice from teams of experts. The challenging adventure of Medical Knowledge Extraction can be followed by ambitious researchers finally resulting in a successful decision support system, that some times is so novel that it will provide new directions for basic or clinical research further that the existed. At least this procedure will save the experience of the best doctors on duty and will help young residents to be better and better.


Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing

Автор: Ron Kohavi, Diane Tang, Ya Xu
Название: Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing
ISBN: 1108724264 ISBN-13(EAN): 9781108724265
Издательство: Cambridge Academ
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Цена: 6758.00 р.
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Описание: Getting numbers is easy; getting trustworthy numbers is hard. From experimentation leaders at Amazon, Google, LinkedIn, and Microsoft, this guide to accelerating innovation using A/B tests includes practical examples, pitfalls, and advice for students and industry professionals, plus deeper dives into advanced topics for experienced practitioners.

Data Mining and Knowledge Discovery for Big Data

Автор: Chu Wesley W.
Название: Data Mining and Knowledge Discovery for Big Data
ISBN: 3642408362 ISBN-13(EAN): 9783642408366
Издательство: Springer
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Цена: 20896.00 р.
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Описание: This book address topics ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction via binary matrix factorization.

Tell Me Why My Children Died: Rabies, Indigenous Knowledge, and Communicative Justice

Автор: Briggs Charles, Mantini-Briggs Clara
Название: Tell Me Why My Children Died: Rabies, Indigenous Knowledge, and Communicative Justice
ISBN: 0822361248 ISBN-13(EAN): 9780822361244
Издательство: Mare Nostrum (Eurospan)
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Цена: 4383.00 р.
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Описание:

Tell Me Why My Children Died tells the gripping story of indigenous leaders' efforts to identify a strange disease that killed thirty-two children and six young adults in a Venezuelan rain forest between 2007 and 2008. In this pathbreaking book, Charles L. Briggs and Clara Mantini-Briggs relay the nightmarish and difficult experiences of doctors, patients, parents, local leaders, healers, and epidemiologists; detail how journalists first created a smoke screen, then projected the epidemic worldwide; discuss the Chávez government's hesitant and sometimes ambivalent reactions; and narrate the eventual diagnosis of bat-transmitted rabies. The book provides a new framework for analyzing how the uneven distribution of rights to produce and circulate knowledge about health are wedded at the hip with health inequities. By recounting residents' quest to learn why their children died and documenting their creative approaches to democratizing health, the authors open up new ways to address some of global health's most intractable problems. 
 
Tell Me Why My Children Died: Rabies, Indigenous Knowledge, and Communicative Justice

Автор: Charles L. Briggs, Clara Mantini-Briggs
Название: Tell Me Why My Children Died: Rabies, Indigenous Knowledge, and Communicative Justice
ISBN: 0822361051 ISBN-13(EAN): 9780822361053
Издательство: Mare Nostrum (Eurospan)
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Цена: 14791.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

Tell Me Why My Children Died tells the gripping story of indigenous leaders' efforts to identify a strange disease that killed thirty-two children and six young adults in a Venezuelan rain forest between 2007 and 2008. In this pathbreaking book, Charles L. Briggs and Clara Mantini-Briggs relay the nightmarish and difficult experiences of doctors, patients, parents, local leaders, healers, and epidemiologists; detail how journalists first created a smoke screen, then projected the epidemic worldwide; discuss the Chávez government's hesitant and sometimes ambivalent reactions; and narrate the eventual diagnosis of bat-transmitted rabies. The book provides a new framework for analyzing how the uneven distribution of rights to produce and circulate knowledge about health are wedded at the hip with health inequities. By recounting residents' quest to learn why their children died and documenting their creative approaches to democratizing health, the authors open up new ways to address some of global health's most intractable problems. 
 
Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data

Автор: Chen
Название: Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data
ISBN: 9811031673 ISBN-13(EAN): 9789811031670
Издательство: Springer
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Цена: 8385.00 р.
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Описание: This book constitutes the refereed proceedings of the first China Conference on Knowledge Graph and Semantic Computing, CCKS, held in Beijing, China, in September 2016.The 19 revised full papers presented together with 6 shared tasks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on knowledge representation and learning; knowledge graph construction and information extraction; linked data and knowledge-based systems; shared tasks.

Big Data Analytics and Knowledge Discovery

Автор: Madria
Название: Big Data Analytics and Knowledge Discovery
ISBN: 3319439456 ISBN-13(EAN): 9783319439457
Издательство: Springer
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Цена: 8106.00 р.
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Описание: The papers are organized in topical sections on Mining Big Data, Applications of Big Data Mining, Big Data Indexing and Searching, Big Data Learning and Security, Graph Databases and Data Warehousing, Data Intelligence and Technology.

Data Mining and Knowledge Discovery for Big Data

Автор: Wesley W. Chu
Название: Data Mining and Knowledge Discovery for Big Data
ISBN: 3662509458 ISBN-13(EAN): 9783662509456
Издательство: Springer
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Цена: 18284.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book address topics ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction via binary matrix factorization.

Towards Analytical Techniques for Optimizing Knowledge Acquisition, Processing, Propagation, and Use in Cyberinfrastructure and Big Data

Автор: L. Octavio Lerma; Vladik Kreinovich
Название: Towards Analytical Techniques for Optimizing Knowledge Acquisition, Processing, Propagation, and Use in Cyberinfrastructure and Big Data
ISBN: 3319613480 ISBN-13(EAN): 9783319613482
Издательство: Springer
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Цена: 16769.00 р.
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Описание: This book describes analytical techniques for optimizing knowledge acquisition, processing, and propagation, especially in the contexts of cyber-infrastructure and big data.

Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data

Автор: Andreas Holzinger; Gabriella Pasi
Название: Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data
ISBN: 3642391451 ISBN-13(EAN): 9783642391453
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book constitutes the refereed proceedings of the Third Workshop on Human-Computer Interaction and Knowledge Discovery, HCI-KDD 2013, held in Maribor, Slovenia, in July 2013, at SouthCHI 2013.

Managing Data From Knowledge Bases: Querying and Extraction

Автор: Wei Emma Zhang; Quan Z. Sheng
Название: Managing Data From Knowledge Bases: Querying and Extraction
ISBN: 3030069400 ISBN-13(EAN): 9783030069407
Издательство: Springer
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Цена: 15372.00 р.
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Описание: In this book, the authors first address the research issues by providing a motivating scenario, followed by the exploration of the principles and techniques of the challenging topics. Then they solve the raised research issues by developing a series of methodologies. More specifically, the authors study the query optimization and tackle the query performance prediction for knowledge retrieval. They also handle unstructured data processing, data clustering for knowledge extraction. To optimize the queries issued through interfaces against knowledge bases, the authors propose a cache-based optimization layer between consumers and the querying interface to facilitate the querying and solve the latency issue. The cache depends on a novel learning method that considers the querying patterns from individual’s historical queries without having knowledge of the backing systems of the knowledge base. To predict the query performance for appropriate query scheduling, the authors examine the queries’ structural and syntactical features and apply multiple widely adopted prediction models. Their feature modelling approach eschews the knowledge requirement on both the querying languages and system.To extract knowledge from unstructured Web sources, the authors examine two kinds of Web sources containing unstructured data: the source code from Web repositories and the posts in programming question-answering communities. They use natural language processing techniques to pre-process the source codes and obtain the natural language elements. Then they apply traditional knowledge extraction techniques to extract knowledge. For the data from programming question-answering communities, the authors make the attempt towards building programming knowledge base by starting with paraphrase identification problems and develop novel features to accurately identify duplicate posts. For domain specific knowledge extraction, the authors propose to use clustering technique to separate knowledge into different groups. They focus on developing a new clustering algorithm that uses manifold constraint in the optimization task and achieves fast and accurate performance.For each model and approach presented in this dissertation, the authors have conducted extensive experiments to evaluate it using either public dataset or synthetic data they generated.

Social Media Data Extraction and Content Analysis

Автор: Shalin Hai-Jew
Название: Social Media Data Extraction and Content Analysis
ISBN: 1522506489 ISBN-13(EAN): 9781522506485
Издательство: Mare Nostrum (Eurospan)
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Цена: 33403.00 р.
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Описание: Explores various social networking platforms and the technologies being utilized to gather and analyse information being posted to these venues. Highlighting emergent research, analytical techniques, and best practices in data extraction in global electronic culture, this publication is an essential reference source for researchers, academics, and professionals.

Big Data Analytics and Knowledge Discovery

Автор: Ladjel Bellatreche; Sharma Chakravarthy
Название: Big Data Analytics and Knowledge Discovery
ISBN: 3319642820 ISBN-13(EAN): 9783319642826
Издательство: Springer
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Цена: 9781.00 р.
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Описание: This book constitutes the refereed proceedings of the 19th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2017, held in Lyon, France, in August 2017. The 24 revised full papers and 11 short papers presented were carefully reviewed and selected from 97 submissions.


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