000 05201nam a22005775i 4500
001 978-3-662-43968-5
003 DE-He213
005 20240730201401.0
007 cr nn 008mamaa
008 140617s2014 gw | s |||| 0|eng d
020 _a9783662439685
_9978-3-662-43968-5
024 7 _a10.1007/978-3-662-43968-5
_2doi
050 4 _aQA76.9.D343
072 7 _aUNF
_2bicssc
072 7 _aUYQE
_2bicssc
072 7 _aCOM021030
_2bisacsh
072 7 _aUNF
_2thema
072 7 _aUYQE
_2thema
082 0 4 _a006.312
_223
245 1 0 _aInteractive Knowledge Discovery and Data Mining in Biomedical Informatics
_h[electronic resource] :
_bState-of-the-Art and Future Challenges /
_cedited by Andreas Holzinger, Igor Jurisica.
250 _a1st ed. 2014.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2014.
300 _aXX, 357 p. 56 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aInformation Systems and Applications, incl. Internet/Web, and HCI,
_x2946-1642 ;
_v8401
505 0 _aKnowledge Discovery and Data Mining in Biomedical Informatics: The Future Is in Integrative, Interactive Machine Learning Solutions -- Visual Data Mining: Effective Exploration of the Biological Universe -- Darwin or Lamarck? Future Challenges in Evolutionary Algorithms for Knowledge Discovery and Data Mining -- On the Generation of Point Cloud Data Sets: Step One in the Knowledge Discovery Process -- Adapted Features and Instance Selection for Improving Co-training -- Knowledge Discovery and Visualization of Clusters for Erythromycin Related Adverse Events in the FDA Drug Adverse Event Reporting System -- On Computationally-Enhanced Visual Analysis of Heterogeneous Data and Its Application in Biomedical Informatics -- A Policy-Based Cleansing and Integration Framework for Labour and Healthcare Data -- Interactive Data Exploration Using Pattern Mining -- Resources for Studying Statistical Analysis of Biomedical Data and R -- A Kernel-Based Framework for Medical Big-Data Analytics -- On Entropy-Based Data Mining -- Sparse Inverse Covariance Estimation for Graph Representation of Feature Structure -- Multi-touch Graph-Based Interaction for Knowledge Discovery on Mobile Devices: State-of-the-Art and Future Challenges -- Intelligent Integrative Knowledge Bases: Bridging Genomics, Integrative Biology and Translational Medicine -- Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges -- Protecting Anonymity in Data-Driven Biomedical Science -- Biobanks - A Source of Large Biological Data Sets: Open Problems and Future Challenges -- On Topological Data Mining.
520 _aOne 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.    .
650 0 _aData mining.
_93907
650 0 _aInformation storage and retrieval systems.
_922213
650 0 _aMedical informatics.
_94729
650 1 4 _aData Mining and Knowledge Discovery.
_9166942
650 2 4 _aInformation Storage and Retrieval.
_923927
650 2 4 _aHealth Informatics.
_931799
700 1 _aHolzinger, Andreas.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9166943
700 1 _aJurisica, Igor.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9166944
710 2 _aSpringerLink (Online service)
_9166945
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783662439678
776 0 8 _iPrinted edition:
_z9783662439692
830 0 _aInformation Systems and Applications, incl. Internet/Web, and HCI,
_x2946-1642 ;
_v8401
_9166946
856 4 0 _uhttps://doi.org/10.1007/978-3-662-43968-5
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
942 _cELN
999 _c96499
_d96499