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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics: State-of-the-Art and Future Challenges: 8401 (Information Systems and Applications, incl. Internet/Web, and HCI) - Tapa blanda
Sinopsis
One of the grand challenges in our digital world are the large, complex and often weakly structured data sets, and massive amounts of unstructured information. This “big data” challenge is most evident in biomedical informatics: the trend towards precision medicine has resulted in an explosion in the amount of generated biomedical data sets. Despite the fact that human experts are very good at pattern recognition in dimensions of <= 3; most of the data is high-dimensional, which makes manual analysis often impossible and neither the medical doctor nor the biomedical researcher can memorize all these facts. A synergistic combination of methodologies and approaches of two fields offer ideal conditions towards unraveling these problems: Human–Computer Interaction (HCI) and Knowledge Discovery/Data Mining (KDD), with the goal of supporting human capabilities with machine learning.
This state-of-the-art survey is an output of the HCI-KDD expert network and features 19 carefully selected and reviewed papers related to seven hot and promising research areas: Area 1: Data Integration, Data Pre-processing and Data Mapping; Area 2: Data Mining Algorithms; Area 3: Graph-based Data Mining; Area 4: Entropy-Based Data Mining; Area 5: Topological Data Mining; Area 6 Data Visualization and Area 7: Privacy, Data Protection, Safety and Security.
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One of the grand challenges in our digital world are the large, complex, and often weakly structured data sets and massive amounts of unstructured information. This big data challenge is most evident in biomedical informatics: The trend toward precision medicine has resulted in an explosion in the amount of biomedical data sets generated. Despite the fact that human experts are very good at pattern recognition in three dimensions or less, most of the data are high-dimensional, which makes manual analysis often impossible and neither the medical doctor nor the biomedical researcher can memorize all these facts. A synergistic combination of the methodologies and approaches of two fields offer ideal conditions for unraveling these problems: human computer interaction (HCI) and knowledge discovery/data mining (KDD), with the goal of supporting human capabilities with machine learning.
This state-of-the-art survey is an output of the HCI-KDD expert network and features 19 carefully selected and reviewed papers related to seven hot and promising research areas: (1) data integration, data pre-processing, and data mapping; (2) data mining algorithms; (3) graph-based data mining; (4) entropy-based data mining; (5) topological data mining; (6) visualization; (7) privacy, data protection, safety, and security.
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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics: State-of-the-Art and Future Challenges (Information Systems and Applications, incl. Internet/Web, and HCI)
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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics : State-of-the-art and Future Challenges
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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics: State-of-the-Art and Future Challenges (Information Systems and Applications, incl. Internet/Web, and HCI)
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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics (Paperback)
Publicado por
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2014
ISBN 10: 3662439670
ISBN 13: 9783662439678
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Paperback. Condición: new. Paperback. One of the grand challenges in our digital world are the large, complex and often weakly structured data sets, and massive amounts of unstructured information. This big data challenge is most evident in biomedical informatics: the trend towards precision medicine has resulted in an explosion in the amount of generated biomedical data sets. Despite the fact that human experts are very good at pattern recognition in dimensions of This state-of-the-art survey is an output of the HCI-KDD expert network and features 19 carefully selected and reviewed papers related to seven hot and promising research areas: Area 1: Data Integration, Data Pre-processing and Data Mapping; Area 2: Data Mining Algorithms; Area 3: Graph-based Data Mining; Area 4: Entropy-Based Data Mining; Area 5: Topological Data Mining; Area 6 Data Visualization and Area 7: Privacy, Data Protection, Safety and Security. One of the grand challenges in our digital world are the large, complex and often weakly structured data sets, and massive amounts of unstructured information. This "big data" challenge is most evident in biomedical informatics: the trend towards precision medicine has resulted in an explosion in the amount of generated biomedical data sets. Despite the fact that human experts are very good at pattern recognition in dimensions of <= 3; most of the data is high-dimensional, which makes manual analysis often impossible and neither the medical doctor nor the biomedical researcher can memorize all these facts. A synergistic combination of methodologies and approaches of two fields offer ideal conditions towards unraveling these problems: Human-Computer Interaction (HCI) and Knowledge Discovery/Data Mining (KDD), with the goal of supporting human capabilities with machine learning.This state-of-the-art survey is an output of the HCI-KDD expert network and features 19 carefully selected and reviewed papers related to seven hot and promising research areas: Area 1: Data Integration, Data Pre-processing and Data Mapping; Area 2: Data Mining Algorithms; Area 3: Graph-based Data Mining; Area 4: Entropy-Based Data Mining; Area 5: Topological Data Mining; Area 6 Data Visualization and Area 7: Privacy, Data Protection, Safety and Security. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9783662439678
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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics: State-of-the-Art and Future Challenges (Information Systems and Applications, incl. Internet/Web, and HCI)
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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics: State-of-the-Art and Future Challenges (Lecture Notes in Computer Science)
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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics
Publicado por
Springer Berlin Heidelberg Jun 2014, 2014
ISBN 10: 3662439670
ISBN 13: 9783662439678
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -One of the grand challenges in our digital world are the large, complex and often weakly structured data sets, and massive amounts of unstructured information. This 'big data' challenge is most evident in biomedical informatics: the trend towards precision medicine has resulted in an explosion in the amount of generated biomedical data sets. Despite the fact that human experts are very good at pattern recognition in dimensions of This state-of-the-art survey is an output of the HCI-KDD expert network and features 19 carefully selected and reviewed papers related to seven hot and promising research areas: Area 1: Data Integration, Data Pre-processing and Data Mapping; Area 2: Data Mining Algorithms; Area 3: Graph-based Data Mining; Area 4: Entropy-Based Data Mining; Area 5: Topological Data Mining; Area 6 Data Visualization and Area 7: Privacy, Data Protection, Safety and Security. 380 pp. Englisch. Nº de ref. del artículo: 9783662439678
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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics : State-of-the-art and Future Challenges
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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics
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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics
Impresión bajo demandaLibrería: Majestic Books, Hounslow, Reino Unido
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