IEICE Trans - Integration of Learning Methods, Medical Literature and Expert Inspection in Medical Data Mining

Integration of Learning Methods, Medical Literature and Expert Inspection in Medical Data Mining

Tu Bao HO
Saori KAWASAKI
Katsuhiko TAKABAYASHI
Canh Hao NGUYEN

Publication
IEICE TRANSACTIONS on Information and Systems Vol.E90-D No.10 pp.1574-1581
Publication Date: 2007/10/01
Online ISSN: 1745-1361
DOI: 10.1093/ietisy/e90-d.10.1574
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Section on Knowledge, Information and Creativity Support System)
Category:
Keyword:
temporal patterns, temporal relations, visualization, expert inspection, integration, hepatitis study,

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Summary:
From lessons learned in medical data mining projects we show that integration of advanced computation techniques and human inspection is indispensable in medical data mining. We proposed an integrated approach that merges data mining and text mining methods plus visualization support for expert evaluation. We also appropriately developed temporal abstraction and text mining methods to exploit the collected data. Furthermore, our visual discovery system D2MS allowed to actively and effectively working with physicians. Significant findings in hepatitis study were obtained by the integrated approach.

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