Simon K Poon (28 results)

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    • Language: English

      Published by Springer, 2014

      3319038001 / 9783319038001

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    • Language: English

      Published by Springer, 2016

      3319346296 / 9783319346298

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    • Language: English

      Published by Springer 2016-09-03, 2016

      3319346296 / 9783319346298

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    • Language: English

      Published by Springer, 2014

      3319038001 / 9783319038001

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    • Language: English

      Published by Springer, 2014

      3319038001 / 9783319038001

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    • Language: English

      Published by Springer, 2014

      3319038001 / 9783319038001

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      Condition: New. pp. 262.

    • Language: English

      Published by Springer, 2016

      3319346296 / 9783319346298

      • Softcover

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      Taschenbuch. Condition: Neu. Data Analytics for Traditional Chinese Medicine Research | Josiah Poon (u. a.) | Taschenbuch | xii | Englisch | 2016 | Springer | EAN 9783319346298 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

    • Language: English

      Published by Springer International Publishing, 2016

      3319346296 / 9783319346298

      • Softcover

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      Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This contributed volume explores how data mining, machine learning, and similar statistical techniques can analyze the types of problems arising from Traditional Chinese Medicine (TCM) research. The book focuses on the study of clinical data and the analysis of herbal data. Challenges addressed include diagnosis, prescription analysis, ingredient discoveries, network based mechanism deciphering, pattern-activity relationships, and medical informatics. Each author demonstrates how they made use of machine learning, data mining, statistics and other analytic techniques to resolve their research challenges, how successful if these techniques were applied, any insight noted and how these insights define the most appropriate future work to be carried out. Readers are given an opportunity to understand the complexity of diagnosis and treatment decision, the difficulty of modeling of efficacy in terms of herbs, the identification of constituent compounds in an herb, the relationship between these compounds and biological outcome so that evidence-based predictions can be made. Drawing on a wide range of experienced contributors, Data Analytics for Traditional Chinese Medicine Research is a valuable reference for professionals and researchers working in health informatics and data mining. The techniques are also useful for biostatisticians and health practitioners interested in traditional medicine and data analytics.

    • Language: English

      Published by Springer International Publishing, 2014

      3319038001 / 9783319038001

      • Hardcover

      Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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      Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This contributed volume explores how data mining, machine learning, and similar statistical techniques can analyze the types of problems arising from Traditional Chinese Medicine (TCM) research. The book focuses on the study of clinical data and the analysis of herbal data. Challenges addressed include diagnosis, prescription analysis, ingredient discoveries, network based mechanism deciphering, pattern-activity relationships, and medical informatics. Each author demonstrates how they made use of machine learning, data mining, statistics and other analytic techniques to resolve their research challenges, how successful if these techniques were applied, any insight noted and how these insights define the most appropriate future work to be carried out. Readers are given an opportunity to understand the complexity of diagnosis and treatment decision, the difficulty of modeling of efficacy in terms of herbs, the identification of constituent compounds in an herb, the relationship between these compounds and biological outcome so that evidence-based predictions can be made. Drawing on a wide range of experienced contributors, Data Analytics for Traditional Chinese Medicine Research is a valuable reference for professionals and researchers working in health informatics and data mining. The techniques are also useful for biostatisticians and health practitioners interested in traditional medicine and data analytics.

    • Language: English

      Published by Springer, 2016

      3319346296 / 9783319346298

      • Softcover

      Seller: Books Puddle, New York, NY, U.S.A.Books Puddle

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      Condition: New. pp. 248.

    • Language: English

      Published by Springer-Verlag New York Inc, 2016

      3319346296 / 9783319346298

      • Softcover

      Seller: Revaluation Books, Exeter, United KingdomRevaluation Books

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      Paperback. Condition: Brand New. reprint edition. 260 pages. 9.25x6.10x0.59 inches. In Stock.

    • Language: English

      Published by Springer, 2014

      3319038001 / 9783319038001

      • Hardcover

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      Condition: Sehr gut. Zustand: Sehr gut | Seiten: 260 | Sprache: Englisch | Produktart: Bücher | This contributed volume explores how data mining, machine learning, and similar statistical techniques can analyze the types of problems arising from Traditional Chinese Medicine (TCM) research. The book focuses on the study of clinical data and the analysis of herbal data. Challenges addressed include diagnosis, prescription analysis, ingredient discoveries, network based mechanism deciphering, pattern-activity relationships, and medical informatics. Each author demonstrates how they made use of machine learning, data mining, statistics and other analytic techniques to resolve their research challenges, how successful if these techniques were applied, any insight noted and how these insights define the most appropriate future work to be carried out. Readers are given an opportunity to understand the complexity of diagnosis and treatment decision, the difficulty of modeling of efficacy in terms of herbs, the identification of constituent compounds in an herb, the relationship between these compounds and biological outcome so that evidence-based predictions can be made. Drawing on a wide range of experienced contributors, Data Analytics for Traditional Chinese Medicine Research is a valuable reference for professionals and researchers working in health informatics and data mining. The techniques are also useful for biostatisticians and health practitioners interested in traditional medicine and data analytics.

    • Language: English

      Published by Springer, 2014

      3319038001 / 9783319038001

      • Hardcover

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    • Language: English

      Published by Springer, 2014

      3319038001 / 9783319038001

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    • Language: English

      Published by Springer, 2014

      3319038001 / 9783319038001

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    • Language: English

      Published by Springer, 2016

      3319346296 / 9783319346298

      • Softcover

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    • Language: English

      Published by Springer, 2014

      3319038001 / 9783319038001

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    • Language: English

      Published by Springer, 2016

      3319346296 / 9783319346298

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    • Language: English

      Published by Springer International Publishing Sep 2016, 2016

      3319346296 / 9783319346298

      • Softcover
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      Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This contributed volume explores how data mining, machine learning, and similar statistical techniques can analyze the types of problems arising from Traditional Chinese Medicine (TCM) research. The book focuses on the study of clinical data and the analysis of herbal data. Challenges addressed include diagnosis, prescription analysis, ingredient discoveries, network based mechanism deciphering, pattern-activity relationships, and medical informatics. Each author demonstrates how they made use of machine learning, data mining, statistics and other analytic techniques to resolve their research challenges, how successful if these techniques were applied, any insight noted and how these insights define the most appropriate future work to be carried out. Readers are given an opportunity to understand the complexity of diagnosis and treatment decision, the difficulty of modeling of efficacy in terms of herbs, the identification of constituent compounds in an herb, the relationship between these compounds and biological outcome so that evidence-based predictions can be made. Drawing on a wide range of experienced contributors, Data Analytics for Traditional Chinese Medicine Research is a valuable reference for professionals and researchers working in health informatics and data mining. The techniques are also useful for biostatisticians and health practitioners interested in traditional medicine and data analytics. 260 pp. Englisch.

    • Language: English

      Published by Springer International Publishing Mrz 2014, 2014

      3319038001 / 9783319038001

      • Hardcover
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      Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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      Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This contributed volume explores how data mining, machine learning, and similar statistical techniques can analyze the types of problems arising from Traditional Chinese Medicine (TCM) research. The book focuses on the study of clinical data and the analysis of herbal data. Challenges addressed include diagnosis, prescription analysis, ingredient discoveries, network based mechanism deciphering, pattern-activity relationships, and medical informatics. Each author demonstrates how they made use of machine learning, data mining, statistics and other analytic techniques to resolve their research challenges, how successful if these techniques were applied, any insight noted and how these insights define the most appropriate future work to be carried out. Readers are given an opportunity to understand the complexity of diagnosis and treatment decision, the difficulty of modeling of efficacy in terms of herbs, the identification of constituent compounds in an herb, the relationship between these compounds and biological outcome so that evidence-based predictions can be made. Drawing on a wide range of experienced contributors, Data Analytics for Traditional Chinese Medicine Research is a valuable reference for professionals and researchers working in health informatics and data mining. The techniques are also useful for biostatisticians and health practitioners interested in traditional medicine and data analytics. 260 pp. Englisch.

    • Language: English

      Published by Springer International Publishing, 2016

      3319346296 / 9783319346298

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      Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a data analytic approach for an efficient way to analyze the data, to find useful patterns, to generate and validate hypothesisOffers data mining researchers a new domain of study, an area which sits on a wealth of data untouched for deve.

    • Language: English

      Published by Springer International Publishing, 2014

      3319038001 / 9783319038001

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      Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a data analytic approach for an efficient way to analyze the data, to find useful patterns, to generate and validate hypothesisOffers data mining researchers a new domain of study, an area which sits on a wealth of data untouched for deve.

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      Published by Springer, 2014

      3319038001 / 9783319038001

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      Condition: New. Print on Demand pp. 262 59 Illus. (45 Col.).

    • Language: English

      Published by Springer, 2014

      3319038001 / 9783319038001

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      Condition: New. PRINT ON DEMAND pp. 262.

    • Language: English

      Published by Springer, Springer Sep 2016, 2016

      3319346296 / 9783319346298

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      Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000

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      Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This contributed volume explores how data mining, machine learning, and similar statistical techniques can analyze the types of problems arising from Traditional Chinese Medicine (TCM) research. The book focuses on the study of clinical data and the analysis of herbal data. Challenges addressed include diagnosis, prescription analysis, ingredient discoveries, network based mechanism deciphering, pattern-activity relationships, and medical informatics. Each author demonstrates how they made use of machine learning, data mining, statistics and other analytic techniques to resolve their research challenges, how successful if these techniques were applied, any insight noted and how these insights define the most appropriate future work to be carried out. Readers are given an opportunity to understand the complexity of diagnosis and treatment decision, the difficulty of modeling of efficacy in terms of herbs, the identification of constituent compounds in an herb, the relationship between these compounds and biological outcome so that evidence-based predictions can be made. Drawing on a wide range of experienced contributors, Data Analytics for Traditional Chinese Medicine Research is a valuable reference for professionals and researchers working in health informatics and data mining. The techniques are also useful for biostatisticians and health practitioners interested in traditional medicine and data analytics.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 260 pp. Englisch.

    • Language: English

      Published by Springer, Springer Mär 2014, 2014

      3319038001 / 9783319038001

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      Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This contributed volume explores how data mining, machine learning, and similar statistical techniques can analyze the types of problems arising from Traditional Chinese Medicine (TCM) research. The book focuses on the study of clinical data and the analysis of herbal data. Challenges addressed include diagnosis, prescription analysis, ingredient discoveries, network based mechanism deciphering, pattern-activity relationships, and medical informatics. Each author demonstrates how they made use of machine learning, data mining, statistics and other analytic techniques to resolve their research challenges, how successful if these techniques were applied, any insight noted and how these insights define the most appropriate future work to be carried out. Readers are given an opportunity to understand the complexity of diagnosis and treatment decision, the difficulty of modeling of efficacy in terms of herbs, the identification of constituent compounds in an herb, the relationship between these compounds and biological outcome so that evidence-based predictions can be made. Drawing on a wide range of experienced contributors, Data Analytics for Traditional Chinese Medicine Research is a valuable reference for professionals and researchers working in health informatics and data mining. The techniques are also useful for biostatisticians and health practitioners interested in traditional medicine and data analytics.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 260 pp. Englisch.

    • Language: English

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      3319346296 / 9783319346298

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      Condition: New. Print on Demand pp. 248.

    • Language: English

      Published by Springer, 2016

      3319346296 / 9783319346298

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      Condition: New. PRINT ON DEMAND pp. 248.