Intelligent Data Analysis in Medicine and Pharmacology:
Intelligent data analysis, data mining and knowledge discovery in databases have recently gained the attention of a large number of researchers and practitioners. This is witnessed by the rapidly increasing number of submissions and participants at related conferences and workshops, by the emergence...
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Weitere Verfasser: | , , |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Boston, MA
Springer US
1997
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Schriftenreihe: | The Springer International Series in Engineering and Computer Science
414 |
Schlagworte: | |
Online-Zugang: | BTU01 Volltext |
Zusammenfassung: | Intelligent data analysis, data mining and knowledge discovery in databases have recently gained the attention of a large number of researchers and practitioners. This is witnessed by the rapidly increasing number of submissions and participants at related conferences and workshops, by the emergence of new journals in this area (e.g., Data Mining and Knowledge Discovery, Intelligent Data Analysis, etc.), and by the increasing number of new applications in this field. In our view, the awareness of these challenging research fields and emerging technologies has been much larger in industry than in medicine and pharmacology. The main purpose of this book is to present the various techniques and methods that are available for intelligent data analysis in medicine and pharmacology, and to present case studies of their application. Intelligent Data Analysis in Medicine and Pharmacology consists of selected (and thoroughly revised) papers presented at the First International Workshop on Intelligent Data Analysis in Medicine and Pharmacology (IDAMAP-96) held in Budapest in August 1996 as part of the 12th European Conference on Artificial Intelligence (ECAI-96), IDAMAP-96 was organized with the motivation to gather scientists and practitioners interested in computational data analysis methods applied to medicine and pharmacology, aimed at narrowing the increasing gap between excessive amounts of data stored in medical and pharmacological databases on the one hand, and the interpretation, understanding and effective use of stored data on the other hand. Besides the revised Workshop papers, the book contains a selection of contributions by invited authors. The expected readership of the book is researchers and practitioners interested in intelligent data analysis, data mining, and knowledge discovery in databases, particularly those who are interested in using these technologies in medicine and pharmacology. Researchers and students in artificial intelligence and statistics should find this book of interest as well. Finally, much of the presented material will be interesting to physicians and pharmacologists challenged by new computational technologies, or simply in need of effectively utilizing the overwhelming volumes of data collected as a result of improved computer support in their daily professional practice |
Beschreibung: | 1 Online-Ressource (XXI, 310 p) |
ISBN: | 9781461560593 |
DOI: | 10.1007/978-1-4615-6059-3 |
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520 | |a Intelligent Data Analysis in Medicine and Pharmacology consists of selected (and thoroughly revised) papers presented at the First International Workshop on Intelligent Data Analysis in Medicine and Pharmacology (IDAMAP-96) held in Budapest in August 1996 as part of the 12th European Conference on Artificial Intelligence (ECAI-96), IDAMAP-96 was organized with the motivation to gather scientists and practitioners interested in computational data analysis methods applied to medicine and pharmacology, aimed at narrowing the increasing gap between excessive amounts of data stored in medical and pharmacological databases on the one hand, and the interpretation, understanding and effective use of stored data on the other hand. Besides the revised Workshop papers, the book contains a selection of contributions by invited authors. | ||
520 | |a The expected readership of the book is researchers and practitioners interested in intelligent data analysis, data mining, and knowledge discovery in databases, particularly those who are interested in using these technologies in medicine and pharmacology. Researchers and students in artificial intelligence and statistics should find this book of interest as well. Finally, much of the presented material will be interesting to physicians and pharmacologists challenged by new computational technologies, or simply in need of effectively utilizing the overwhelming volumes of data collected as a result of improved computer support in their daily professional practice | ||
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Datensatz im Suchindex
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any_adam_object | |
author2 | Lavrač, Nada Keravnou, Elpida T. Zupan, Blaž |
author2_role | edt edt edt |
author2_variant | n l nl e t k et etk b z bz |
author_facet | Lavrač, Nada Keravnou, Elpida T. Zupan, Blaž |
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discipline | Informatik |
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spelling | Intelligent Data Analysis in Medicine and Pharmacology edited by Nada Lavrač, Elpida T. Keravnou, Blaž Zupan Boston, MA Springer US 1997 1 Online-Ressource (XXI, 310 p) txt rdacontent c rdamedia cr rdacarrier The Springer International Series in Engineering and Computer Science 414 Intelligent data analysis, data mining and knowledge discovery in databases have recently gained the attention of a large number of researchers and practitioners. This is witnessed by the rapidly increasing number of submissions and participants at related conferences and workshops, by the emergence of new journals in this area (e.g., Data Mining and Knowledge Discovery, Intelligent Data Analysis, etc.), and by the increasing number of new applications in this field. In our view, the awareness of these challenging research fields and emerging technologies has been much larger in industry than in medicine and pharmacology. The main purpose of this book is to present the various techniques and methods that are available for intelligent data analysis in medicine and pharmacology, and to present case studies of their application. Intelligent Data Analysis in Medicine and Pharmacology consists of selected (and thoroughly revised) papers presented at the First International Workshop on Intelligent Data Analysis in Medicine and Pharmacology (IDAMAP-96) held in Budapest in August 1996 as part of the 12th European Conference on Artificial Intelligence (ECAI-96), IDAMAP-96 was organized with the motivation to gather scientists and practitioners interested in computational data analysis methods applied to medicine and pharmacology, aimed at narrowing the increasing gap between excessive amounts of data stored in medical and pharmacological databases on the one hand, and the interpretation, understanding and effective use of stored data on the other hand. Besides the revised Workshop papers, the book contains a selection of contributions by invited authors. The expected readership of the book is researchers and practitioners interested in intelligent data analysis, data mining, and knowledge discovery in databases, particularly those who are interested in using these technologies in medicine and pharmacology. Researchers and students in artificial intelligence and statistics should find this book of interest as well. Finally, much of the presented material will be interesting to physicians and pharmacologists challenged by new computational technologies, or simply in need of effectively utilizing the overwhelming volumes of data collected as a result of improved computer support in their daily professional practice Computer Science Data Structures, Cryptology and Information Theory Biomedicine general Artificial Intelligence (incl. Robotics) Pharmacology/Toxicology Statistics for Life Sciences, Medicine, Health Sciences Computer science Pharmacology Data structures (Computer science) Artificial intelligence Statistics Pharmakologie (DE-588)4045687-0 gnd rswk-swf Datenanalyse (DE-588)4123037-1 gnd rswk-swf 1\p (DE-588)1071861417 Konferenzschrift gnd-content 2\p (DE-588)4143413-4 Aufsatzsammlung gnd-content Pharmakologie (DE-588)4045687-0 s Datenanalyse (DE-588)4123037-1 s 3\p DE-604 Lavrač, Nada edt Keravnou, Elpida T. edt Zupan, Blaž edt Erscheint auch als Druck-Ausgabe 9781461377757 https://doi.org/10.1007/978-1-4615-6059-3 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
spellingShingle | Intelligent Data Analysis in Medicine and Pharmacology Computer Science Data Structures, Cryptology and Information Theory Biomedicine general Artificial Intelligence (incl. Robotics) Pharmacology/Toxicology Statistics for Life Sciences, Medicine, Health Sciences Computer science Pharmacology Data structures (Computer science) Artificial intelligence Statistics Pharmakologie (DE-588)4045687-0 gnd Datenanalyse (DE-588)4123037-1 gnd |
subject_GND | (DE-588)4045687-0 (DE-588)4123037-1 (DE-588)1071861417 (DE-588)4143413-4 |
title | Intelligent Data Analysis in Medicine and Pharmacology |
title_auth | Intelligent Data Analysis in Medicine and Pharmacology |
title_exact_search | Intelligent Data Analysis in Medicine and Pharmacology |
title_full | Intelligent Data Analysis in Medicine and Pharmacology edited by Nada Lavrač, Elpida T. Keravnou, Blaž Zupan |
title_fullStr | Intelligent Data Analysis in Medicine and Pharmacology edited by Nada Lavrač, Elpida T. Keravnou, Blaž Zupan |
title_full_unstemmed | Intelligent Data Analysis in Medicine and Pharmacology edited by Nada Lavrač, Elpida T. Keravnou, Blaž Zupan |
title_short | Intelligent Data Analysis in Medicine and Pharmacology |
title_sort | intelligent data analysis in medicine and pharmacology |
topic | Computer Science Data Structures, Cryptology and Information Theory Biomedicine general Artificial Intelligence (incl. Robotics) Pharmacology/Toxicology Statistics for Life Sciences, Medicine, Health Sciences Computer science Pharmacology Data structures (Computer science) Artificial intelligence Statistics Pharmakologie (DE-588)4045687-0 gnd Datenanalyse (DE-588)4123037-1 gnd |
topic_facet | Computer Science Data Structures, Cryptology and Information Theory Biomedicine general Artificial Intelligence (incl. Robotics) Pharmacology/Toxicology Statistics for Life Sciences, Medicine, Health Sciences Computer science Pharmacology Data structures (Computer science) Artificial intelligence Statistics Pharmakologie Datenanalyse Konferenzschrift Aufsatzsammlung |
url | https://doi.org/10.1007/978-1-4615-6059-3 |
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