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  • English  (73)
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Type of Publication
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  • 1
    UID:
    (DE-101)1217415491
    Format: Online-Ressource
    ISSN: 0976-5050
    In: volume:11
    In: number:02
    In: year:2020
    In: pages:099-105
    In: Journal of Digestive Endoscopy, [Noida] : Thieme Medical and Scientific Publishers, 2011-, 11, Heft 02 (2020), 099-105, 0976-5050
    Language: English
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  • 2
    UID:
    (DE-101)1119196523
    Format: Online-Ressource , online resource.
    ISSN: 0975-0711 , 0975-0711
    In: volume:35
    In: number:5
    In: day:28
    In: month:9
    In: year:2016
    In: pages:397
    In: date:9.2016
    In: Indian journal of gastroenterology, [New Delhi] : Springer India, 1982-, 35, Heft 5 (28.9.2016), 397, 9.2016, 0975-0711
    Language: English
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  • 3
    UID:
    (DE-101)1199877387
    Format: Online-Ressource
    ISSN: 0976-5050
    In: volume:04
    In: number:04
    In: year:2013
    In: pages:099-102
    In: Journal of Digestive Endoscopy, [Noida] : Thieme Medical and Scientific Publishers, 2011-, 04, Heft 04 (2013), 099-102, 0976-5050
    Language: English
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  • 4
    UID:
    (DE-101)1325830224
    Format: Online-Ressource
    ISSN: 0976-5050
    Content: Abstract: Per-oral endoscopic myotomy (POEM) is one of the main modalities of treatment of achalasia cardia today across subtypes and we are increasingly seeing patients persistent or recurrent symptoms after POEM. An accurate high-resolution esophageal manometry (HREM) is one of the most important tests that can help us guide the treatment in cases of failure of POEM. HREM can help us direct the therapy. The therapy can be lower esophageal sphincter-directed therapy or esophageal body-directed therapy that can be ascertained using HREM. With this review, we detail the factors associated with failure of POEM, tests that can be utilized for its evaluation, and case-based analysis using HREM in patients of post-POEM failure.
    In: day:21
    In: month:02
    In: year:2024
    In: Journal of Digestive Endoscopy, [Noida] : Thieme Medical and Scientific Publishers, 2011-, (21.02.2024), 0976-5050
    Language: English
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  • 5
    UID:
    (DE-101)1199269204
    Format: Online-Ressource
    ISSN: 0976-5050
    In: volume:10
    In: number:01
    In: year:2019
    In: pages:001-002
    In: Journal of Digestive Endoscopy, [Noida] : Thieme Medical and Scientific Publishers, 2011-, 10, Heft 01 (2019), 001-002, 0976-5050
    Language: English
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  • 6
    Online Resource
    Online Resource
    San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool
    UID:
    (DE-627)165674192X
    Format: Online-Ressource (x, 114 pages)
    ISBN: 9781627058360
    Series Statement: Synthesis lectures on computer architecture # 35
    Content: This book aims to achieve the following goals: (1) to provide a high-level survey of key analytics models and algorithms without going into mathematical details; (2) to analyze the usage patterns of these models; and (3) to discuss opportunities for accelerating analytics workloads using software, hardware, and system approaches. The book first describes 14 key analytics models (exemplars) that span data mining, machine learning, and data management domains. For each analytics exemplar, we summarize its computational and runtime patterns and apply the information to evaluate parallelization and acceleration alternatives for that exemplar. Using case studies from important application domains such as deep learning, text analytics, and business intelligence (BI), we demonstrate how various software and hardware acceleration strategies are implemented in practice. This book is intended for both experienced professionals and students who are interested in understanding core algorithms behind analytics workloads. It is designed to serve as a guide for addressing various open problems in accelerating analytics workloads, e.g., new architectural features for supporting analytics workloads, impact on programming models and runtime systems, and designing analytics systems.
    Note: Part of: Synthesis digital library of engineering and computer science. - Includes bibliographical references (pages 79-111). - Compendex. INSPEC. Google scholar. Google book search. - Title from PDF title page (viewed on November 24, 2015) , 1. Introduction -- 1.1 Analytics: a definition -- 1.2 Analytics at your service -- 1.3 Classification of analytics applications -- 1.3.1 The Watson DeepQA system -- 1.3.2 Functional flow of analytics applications -- 1.4 Intended audience -- , Mode of access: World Wide Web. , System requirements: Adobe Acrobat Reader.
    Additional Edition: 9781627058353
    Additional Edition: Erscheint auch als Druck-Ausgabe 9781627058353
    Language: English
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  • 7
    Online Resource
    Online Resource
    [San Rafael] : Morgan & Claypool Publishers
    UID:
    (DE-627)855976160
    Format: 1 Online-Ressource (x, 114 Seiten)
    Edition: Also available in print
    ISBN: 1627058362 , 9781627058360
    Series Statement: Synthesis lectures on computer architecture #35
    Content: This book aims to achieve the following goals: (1) to provide a high-level survey of key analytics models and algorithms without going into mathematical details; (2) to analyze the usage patterns of these models; and (3) to discuss opportunities for accelerating analytics workloads using software, hardware, and system approaches. The book first describes 14 key analytics models (exemplars) that span data mining, machine learning, and data management domains. For each analytics exemplar, we summarize its computational and runtime patterns and apply the information to evaluate parallelization and acceleration alternatives for that exemplar. Using case studies from important application domains such as deep learning, text analytics, and business intelligence (BI), we demonstrate how various software and hardware acceleration strategies are implemented in practice. This book is intended for both experienced professionals and students who are interested in understanding core algorithms behind analytics workloads. It is designed to serve as a guide for addressing various open problems in accelerating analytics workloads, e.g., new architectural features for supporting analytics workloads, impact on programming models and runtime systems, and designing analytics systems
    Content: 1. Introduction -- 1.1 Analytics: a definition -- 1.2 Analytics at your service -- 1.3 Classification of analytics applications -- 1.3.1 The Watson DeepQA system -- 1.3.2 Functional flow of analytics applications -- 1.4 Intended audience --
    Content: 2. Overview of analytics exemplars -- 2.1 Exemplar models -- 2.2 Regression analysis -- 2.3 Clustering -- 2.4 Nearest neighbor search -- 2.5 Association rule mining -- 2.6 Recommender systems -- 2.7 Support vector machines -- 2.8 Neural networks -- 2.9 Decision tree learning -- 2.10 Time series processing -- 2.11 Text analytics -- 2.12 Monte Carlo methods -- 2.13 Mathematical programming -- 2.14 On-line analytical processing -- 2.15 Graph analytics --
    Content: 3. Accelerating analytics -- 3.1 Characterizing analytics exemplars -- 3.1.1 Computational patterns -- 3.1.2 Runtime characteristics -- 3.2 Implications on acceleration -- 3.2.1 System acceleration opportunities --
    Content: 4. Accelerating analytics in practice: case studies -- 4.1 Text analytics -- 4.2 Deep learning -- 4.3 Computational finance -- 4.4 OLAP/business intelligence -- 4.5 Graph analytics --
    Content: 5. Architectural desiderata for analytics -- 5.1 Accelerators for analytics workloads -- 5.2 Bringing it all together: building an analytics system --
    Content: A. Examples of industrial sectors and associated analytical solutions -- Bibliography -- Authors' biographies
    Note: Includes bibliographical references (pages 79-111) , Also available in print. , Mode of access: World Wide Web. , System requirements: Adobe Acrobat Reader.
    Additional Edition: 1627058354
    Additional Edition: 9781627058353
    Additional Edition: Erscheint auch als Druck-Ausgabe 9781627058353
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 8
    Online Resource
    Online Resource
    San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool
    UID:
    (DE-602)gbv_165674192X
    Format: Online-Ressource (x, 114 pages)
    ISBN: 9781627058360
    Series Statement: Synthesis lectures on computer architecture # 35
    Content: This book aims to achieve the following goals: (1) to provide a high-level survey of key analytics models and algorithms without going into mathematical details; (2) to analyze the usage patterns of these models; and (3) to discuss opportunities for accelerating analytics workloads using software, hardware, and system approaches. The book first describes 14 key analytics models (exemplars) that span data mining, machine learning, and data management domains. For each analytics exemplar, we summarize its computational and runtime patterns and apply the information to evaluate parallelization and acceleration alternatives for that exemplar. Using case studies from important application domains such as deep learning, text analytics, and business intelligence (BI), we demonstrate how various software and hardware acceleration strategies are implemented in practice. This book is intended for both experienced professionals and students who are interested in understanding core algorithms behind analytics workloads. It is designed to serve as a guide for addressing various open problems in accelerating analytics workloads, e.g., new architectural features for supporting analytics workloads, impact on programming models and runtime systems, and designing analytics systems.
    Note: Part of: Synthesis digital library of engineering and computer science. - Includes bibliographical references (pages 79-111). - Compendex. INSPEC. Google scholar. Google book search. - Title from PDF title page (viewed on November 24, 2015) , 1. Introduction -- 1.1 Analytics: a definition -- 1.2 Analytics at your service -- 1.3 Classification of analytics applications -- 1.3.1 The Watson DeepQA system -- 1.3.2 Functional flow of analytics applications -- 1.4 Intended audience -- , Mode of access: World Wide Web. , System requirements: Adobe Acrobat Reader.
    Additional Edition: ISBN 9781627058353
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9781627058353
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 9
    UID:
    (DE-101)1199834416
    Format: Online-Ressource
    ISSN: 0976-5050
    In: volume:08
    In: number:01
    In: year:2017
    In: pages:44-45
    In: Journal of Digestive Endoscopy, [Noida] : Thieme Medical and Scientific Publishers, 2011-, 08, Heft 01 (2017), 44-45, 0976-5050
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 10
    Online Resource
    Online Resource
    San Rafael : Morgan & Claypool Publishers
    UID:
    (DE-627)847694666
    Format: Online-Ressource (126 p)
    ISBN: 9781627058360
    Series Statement: Synthesis Lectures on Computer Architecture
    Content: Intro -- Introduction -- Analytics: A Definition -- Analytics at Your Service -- Classification of Analytics Applications -- The Watson DeepQA System -- Functional Flow of Analytics Applications -- Intended Audience -- Overview of Analytics Exemplars -- Exemplar Models -- Regression Analysis -- Clustering -- Nearest Neighbor Search -- Association Rule Mining -- Recommender Systems -- Support Vector Machines -- Neural Networks -- Decision Tree Learning -- Time Series Processing -- Text Analytics -- Monte Carlo Methods -- Mathematical Programming -- On-line Analytical Processing -- Graph Analytics -- Accelerating Analytics -- Characterizing Analytics Exemplars -- Computational Patterns -- Runtime Characteristics -- Implications on Acceleration -- System Acceleration Opportunities -- Accelerating Analytics in Practice: Case Studies -- Text Analytics -- Deep Learning -- Computational Finance -- OLAP/Business Intelligence -- Graph Analytics -- Architectural Desiderata for Analytics -- Accelerators for Analytics Workloads -- Bringing it all together: Building an Analytics System -- Examples of Industrial Sectors and Associated Analytical Solutions -- Bibliography -- Authors' Biographies.
    Note: Description based upon print version of record , Introduction -- Analytics: A Definition -- Analytics at Your Service -- Classification of Analytics Applications -- The Watson DeepQA System -- Functional Flow of Analytics Applications -- Intended Audience -- Overview of Analytics Exemplars -- Exemplar Models -- Regression Analysis -- Clustering -- Nearest Neighbor Search -- Association Rule Mining -- Recommender Systems -- Support Vector Machines -- Neural Networks -- Decision Tree Learning -- Time Series Processing -- Text Analytics -- Monte Carlo Methods -- Mathematical Programming -- On-line Analytical Processing -- Graph Analytics , Accelerating Analytics -- Characterizing Analytics Exemplars -- Computational Patterns -- Runtime Characteristics -- Implications on Acceleration -- System Acceleration Opportunities -- Accelerating Analytics in Practice: Case Studies -- Text Analytics -- Deep Learning -- Computational Finance -- OLAP/Business Intelligence -- Graph Analytics -- Architectural Desiderata for Analytics -- Accelerators for Analytics Workloads -- Bringing it all together: Building an Analytics System -- Examples of Industrial Sectors and Associated Analytical Solutions -- Bibliography -- Authors' Biographies , Blank Page
    Additional Edition: 9781627058360
    Additional Edition: 9781627058353
    Additional Edition: Print version Bordawekar, Rajesh Analyzing Analytics San Rafael : Morgan & Claypool Publishers,c2015
    Language: English
    Keywords: Electronic books
    URL: Volltext  (lizenzpflichtig)
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