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 | 2013 | |
|---|---|---|
| j17 |      | |
| 2012 | ||
| c102 | | Shusaku Tsumoto, Haruko Iwata, Shoji Hirano, Yuko Tsumoto: Exploratory temporal data mining process in hospital information systems. ICCI*CC 2012: 145-152 |
| c101 | | Shusaku Tsumoto, Haruko Iwata, Shoji Hirano: Construction and maintenance of clinical pathways using data mining methods. MIX-HS 2012: 47-52 |
| c100 | | Haruko Iwata, Shusaku Tsumoto, Shoji Hirano: Data-Oriented Construction and Maintenance of Clinical Pathway Using Similarity-Based Data Mining Methods. ICDM Workshops 2012: 293-300 |
| c99 | | |
| c98 | | Shusaku Tsumoto, Shoji Hirano: Incremental Rules Induction Method Based on Three Rule Layers. ISMIS 2012: 71-80 |
| c97 | | |
| c96 | | Shusaku Tsumoto, Shoji Hirano: Trajectories mining in hospital information systems. SMC 2012: 389-394 |
| c95 | | Shusaku Tsumoto, Shoji Hirano: Information granules in medical differential diagnosis. SMC 2012: 395-401 |
| c94 | | Shusaku Tsumoto, Shoji Hirano, Haruko Iwata: Data-oriented maintenance of clinical pathway using clustering and multidimensional scaling. SMC 2012: 2596-2600 |
| c93 | | Shusaku Tsumoto, Shoji Hirano, Haruko Iwata, Yuko Tsumoto: Characterizing Hospital Services Using Temporal Data Mining. SRII Global Conference 2012: 219-230 |
| 2011 | ||
| j16 | | Shusaku Tsumoto, Shoji Hirano: Detection of risk factors using trajectory mining. J. Intell. Inf. Syst. 36(3): 403-425 (2011) |
| c92 | | Shusaku Tsumoto, Shoji Hirano, Haruko Iwata, Yuko Tsumoto: Capturing Behavior of Medical Staff: A Similarity-Oriented Temporal Data Mining Approach. FGIT 2011: 1-16 |
| c91 | | Shoji Hirano, Shusaku Tsumoto: A clustering method for asymmetric proximity data based on bi-links with ε-indiscernibility. GrC 2011: 242-245 |
| c90 | | Shusaku Tsumoto, Shoji Hirano, Yuko Tsumoto: Clustering-based analysis in hospital information systems. GrC 2011: 669-674 |
| c89 | | Shusaku Tsumoto, Shoji Hirano: Combinatorics of pearson residuals and degree of freedom in contingency tables. GrC 2011: 675-680 |
| c88 | | Shusaku Tsumoto, Shoji Hirano, Yuko Tsumoto: Visualization of Hospital Services Using Data Mining Methods. ICDM Workshops 2011: 1183-1190 |
| c87 | | Shusaku Tsumoto, Shoji Hirano, Yuko Tsumoto: Information reuse in hospital information systems: A data mining approach. IRI 2011: 172-176 |
| c86 | | Shusaku Tsumoto, Shoji Hirano: Information Reuse in Hospital Information Systems: A Similarity-Oriented Data Mining Approach. RSKT 2011: 382-387 |
| c85 | | Shusaku Tsumoto, Shoji Hirano, Hidenao Abe, Yuko Tsumoto: Temporal data mining in history data of hospital information systems. SMC 2011: 2350-2356 |
| 2010 | ||
| j15 | | Shusaku Tsumoto, Shoji Hirano: Risk Mining in Medicine: Application of Data Mining to Medical Risk Management. Fundam. Inform. 98(1): 107-121 (2010) |
| j14 | | Shoji Hirano, Shusaku Tsumoto: Multiscale Comparison and Clustering of Three-Dimensional Trajectories Based on Curvature Maxima. International Journal of Information Technology and Decision Making 9(6): 889-904 (2010) |
| c84 | | Shusaku Tsumoto, Shoji Hirano, Hidenao Abe: Sampling from databases for rule induction methods based on likelihood ratio test. IEEE ICCI 2010: 174-179 |
| c83 | | Shoji Hirano, Shusaku Tsumoto: Hierarchical, Granular Representation of Non-metric Proximity Data. GrC 2010: 217-222 |
| c82 | | Shusaku Tsumoto, Shoji Hirano: Information Granules of Statistical Dependence in Multiway Contingency Tables. GrC 2010: 483-488 |
| c81 | | Shusaku Tsumoto, Shoji Hirano: Geometrical and Combinatorial Nature of Pearson Residuals. GrC 2010: 489-494 |
| c80 | | Shoji Hirano, Shusaku Tsumoto: Curvature Maxima-based Trajectories Mining. ICDM Workshops 2010: 257-264 |
| c79 | | Shusaku Tsumoto, Shoji Hirano: Automated Empirical Selection of Rule Induction Methods Based on Recursive Iteration of Resampling Methods and Multiple Testing. ICDM Workshops 2010: 835-842 |
| c78 | | Shusaku Tsumoto, Shoji Hirano, Yuko Tsumoto: Towards Data-Oriented Hospital Services: Data Mining-Based Hospital Management. ICDM Workshops 2010: 1076-1083 |
| c77 | | Shusaku Tsumoto, Shoji Hirano, Hidenao Abe: Automated Empirical Selection of Rule Induction Methods Based on Recursive Iteration of Resampling Methods. Intelligent Information Processing 2010: 139-144 |
| c76 | | Shoji Hirano, Shusaku Tsumoto: Representation of Granularity for Non-Euclidian Relational Data by Jaccard Coefficients and Binary Classifications. RSCTC 2010: 721-729 |
| c75 | | Shusaku Tsumoto, Shoji Hirano, Hidenao Abe: Likelihood-Based Sampling from Databases for Rule Induction Methods. RSKT 2010: 265-272 |
| c74 | | Shusaku Tsumoto, Shoji Hirano: Residual Analysis of Statistical Dependence in Multiway Contingency Tables. RSKT 2010: 273-280 |
| c73 | | Shoji Hirano, Shusaku Tsumoto: Multiscale Comparison of Three-Dimensional Trajectories Based on the Curvature Maxima and Its Application to Medicine. SBP 2010: 128-137 |
| c72 | | |
| 2009 | ||
| j13 | | Shusaku Tsumoto, Shoji Hirano: Statistical Independence and Determinants in a Contingency Table - Interpretation of Pearson Residuals based on Linear Algebra -. Fundam. Inform. 90(3): 251-267 (2009) |
| j12 | | Shusaku Tsumoto, Shoji Hirano: Contingency Matrix Theory II: Degree of Dependence as Granularity. Fundam. Inform. 90(4): 427-442 (2009) |
| c71 | | Shusaku Tsumoto, Shoji Hirano, Hidenao Abe: Multivariate statistical independence and contingency tables. GrC 2009: 544-548 |
| c70 | | Shoji Hirano, Shusaku Tsumoto: Multiscale Comparison of Three-Dimensional Trajectories: A Preliminary Step. RSFDGrC 2009: 361-368 |
| c69 | | Shusaku Tsumoto, Shoji Hirano, Hidenao Abe: Pearson Residuals in Multi-way Contingency Tables. SMC 2009: 2531-2536 |
| r1 | | Shusaku Tsumoto, Shoji Hirano: Dependency and Granularity inData. Encyclopedia of Complexity and Systems Science 2009: 1864-1872 |
| 2008 | ||
| j11 | | Shusaku Tsumoto, Shoji Hirano: Contingency Matrix Theory I: Rank and Statistical Independence in a Contigency Table. Transactions on Computational Science 2: 161-179 (2008) |
| c68 | | Shusaku Tsumoto, Shoji Hirano: Fuzziness from attribute generalization in information table. IEEE ICCI 2008: 455-461 |
| c67 | | Shusaku Tsumoto, Shoji Hirano: Statistical independence in three-variables contingency cube. IEEE ICCI 2008: 468-474 |
| c66 | | Shusaku Tsumoto, Shoji Hirano: Mining Trajectories of Laboratory Data using Multiscale Matching and Clustering. CBMS 2008: 626-631 |
| c65 | | Shusaku Tsumoto, Shoji Hirano: Partial statistical independence in contingency matrix. FUZZ-IEEE 2008: 2412-2419 |
| c64 | | Shoji Hirano, Shusaku Tsumoto: Trajectory mining using multiscale matching and clustering. FUZZ-IEEE 2008: 2420-2427 |
| c63 | | Shusaku Tsumoto, Shoji Hirano: Decomposition of Pearson Residuals of Three-variables Contingency Cube. GrC 2008: 61-66 |
| c62 | | Shoji Hirano, Shusaku Tsumoto: Hierarchical Clustering of Asymmetric Proximity Data based on the Indiscernibility-level. GrC 2008: 275-280 |
| c61 | | Shusaku Tsumoto, Shoji Hirano: Statistical Independence and Contingency Matrix. ICDM Workshops 2008: 643-648 |
| c60 | | |
| c59 | | Shoji Hirano, Shusaku Tsumoto: Detection of Risk Factors as Temporal Data Mining. PAKDD Workshops 2008: 143-156 |
| c58 | | Shusaku Tsumoto, Shoji Hirano: Statistical Independence of Multi-variables from the Viewpoint of Linear Algebra. RSCTC 2008: 103-112 |
| c57 | | Shoji Hirano, Shusaku Tsumoto: Hierarchical Clustering of Non-Euclidean Relational Data Using Indiscernibility-Level. RSKT 2008: 332-339 |
| c56 | | |
| p1 | | Shoji Hirano, Shusaku Tsumoto: Discovery of Clusters from Proximity Data: An Approach Using Iterative Adjustment of Binary Classifications. Communications and Discoveries from Multidisciplinary Data 2008: 251-268 |
| 2007 | ||
| j10 | | Shusaku Tsumoto, Shoji Hirano: Visualization of Differences between Rules' Syntactic and Semantic Similarities using Multidimensional Scaling. Fundam. Inform. 78(4): 561-573 (2007) |
| j9 | | Shusaku Tsumoto, Shoji Hirano: Detection of interesting rules using visualization of differences between rules' syntactic and semantic similarities using multidimensional scaling. KES Journal 11(5): 345-354 (2007) |
| c55 | | Shusaku Tsumoto, Shoji Hirano: Charcteristics of Pearson Residuals in a Contingency Matrix. IEEE ICCI 2007: 195-204 |
| c54 | | Shoji Hirano, Shusaku Tsumoto: Trajectory Analysis of Laboratory Tests as Medical Complex Data Mining. MCD 2007: 27-41 |
| c53 | | Shusaku Tsumoto, Shoji Hirano: Meaning of Pearson Residuals - Linear Algebra View. GrC 2007: 465-470 |
| c52 | | Shoji Hirano, Shusaku Tsumoto: Identifying Exacerbating Cases in Chronic Diseases Based on the Cluster Analysis of Trajectory Data on Laboratory Examinations. ICDM Workshops 2007: 151-156 |
| c51 | | Shoji Hirano, Shusaku Tsumoto: Discovery of Risky Cases in Chronic Diseases: An Approach Using Trajectory Grouping. JSAI 2007: 289-302 |
| c50 | | Shusaku Tsumoto, Shoji Hirano: Visualization of Similarities and Dissimilarities Between Rules Using Multidimensional Scaling. KES (2) 2007: 978-986 |
| c49 | | Shoji Hirano, Shusaku Tsumoto: Dealing with granularity on non-euclidean relational data based on indiscernibility level. SMC 2007: 3772-3777 |
| c48 | | |
| 2006 | ||
| c47 | | Shusaku Tsumoto, Shoji Hirano: Analysis of sample size effect on dependency of contingency matrix. GrC 2006: 712-715 |
| c46 | | Shusaku Tsumoto, Shoji Hirano: Characterization of contextual independence of contingency matrix. GrC 2006: 716-719 |
| c45 | | Shusaku Tsumoto, Shoji Hirano: Residual Matrix and Statistical Independence in a Contingency Table. ICDM Workshops 2006: 433-437 |
| c44 | | Shoji Hirano, Shusaku Tsumoto: Cluster Analysis of Time-Series Medical Data Based on the Trajectory Representation and Multiscale Comparison Techniques. ICDM 2006: 896-901 |
| c43 | | Shoji Hirano, Shusaku Tsumoto: Characteristics of Indiscernibility Degree in Rough Clustering Examined Using Perfect Initial Equivalence Relations. ISMIS 2006: 454-462 |
| c42 | | Shusaku Tsumoto, Shoji Hirano: Distribution of Determinants of Contingency Matrix. RSCTC 2006: 567-576 |
| c41 | | Shusaku Tsumoto, Shoji Hirano: Interpretation of Contingency Matrix Using Marginal Distributions. RSCTC 2006: 577-586 |
| c40 | | Shoji Hirano, Shusaku Tsumoto: A Framework for Unsupervised Selection of Indiscernibility Threshold in Rough Clustering. RSCTC 2006: 872-881 |
| c39 | | Shoji Hirano, Shusaku Tsumoto: On the Nature of Degree of Indiscerniblity for Rough Clustering. SMC 2006: 3447-3452 |
| c38 | | Shusaku Tsumoto, Shoji Hirano: Meaning of Marginal Distributions in a Contingency Table. SMC 2006: 4753-4758 |
| e1 |  | Salvatore Greco, Yutaka Hata, Shoji Hirano, Masahiro Inuiguchi, Sadaaki Miyamoto, Hung Son Nguyen, Roman Slowinski (Eds.): Rough Sets and Current Trends in Computing, 5th International Conference, RSCTC 2006, Kobe, Japan, November 6-8, 2006, Proceedings. Lecture Notes in Computer Science 4259, Springer 2006, isbn 3-540-47693-8 |
| 2005 | ||
| j8 | | Shoji Hirano, Shusaku Tsumoto: Rough representation of a region of interest in medical images. Int. J. Approx. Reasoning 40(1-2): 23-34 (2005) |
| j7 | | Shusaku Tsumoto, Shoji Hirano: Automated discovery of chronological patterns in long time-series medical datasets. Int. J. Intell. Syst. 20(7): 737-757 (2005) |
| c37 | | Shusaku Tsumoto, Shoji Hirano: Degree of Dependence as Granularity in a Contingency Table. GrC 2005: 63-69 |
| c36 | | |
| c35 | | |
| c34 | | Shoji Hirano, Shusaku Tsumoto: Grouping of Soccer Game Records by Multiscale Comparison Technique and Rough Clustering. HIS 2005: 399-404 |
| c33 | | Shusaku Tsumoto, Shoji Hirano: Visualization of Similarities and Dissimilarities in Rules Using Multidimensional Scaling. ISMIS 2005: 38-46 |
| c32 | | Shoji Hirano, Shusaku Tsumoto: Clustering Time-Series Medical Databases Based on the Improved Multiscale Matching. ISMIS 2005: 612-621 |
| c31 | | Shoji Hirano, Shusaku Tsumoto: On Constructing Clusters from Non-Euclidean Dissimilarity Matrix by Using Rough Clustering. JSAI Workshops 2005: 5-16 |
| c30 | | Shusaku Tsumoto, Shoji Hirano: On Degree of Dependence Based on Contingency Matrix. RSFDGrC (1) 2005: 471-480 |
| c29 | | Shoji Hirano, Shusaku Tsumoto: A Clustering Method for Spatio-temporal Data and Its Application to Soccer Game Records. RSFDGrC (1) 2005: 612-621 |
| c28 | | Shoji Hirano, Shusaku Tsumoto: A Parallel, Structural Comparison Scheme of Time-Series Implemented on a PC Cluster. SAINT Workshops 2005: 344-347 |
| c27 | | Shoji Hirano, Shusaku Tsumoto: Strucutural Comparison and Cluster Analysis of Time-Series Medical Data. SMC 2005: 1506-1511 |
| c26 | | Shusaku Tsumoto, Shoji Hirano, Hidenao Abe, Hideaki Nakakuni, Eisuke Hanada: Clinical Decision Support Based on Mobile Telecommunication Systems. Web Intelligence 2005: 700-703 |
| 2004 | ||
| j6 | | Shoji Hirano, Xiaoguang Sun, Shusaku Tsumoto: Comparison of clustering methods for clinical databases. Inf. Sci. 159(2): 155-165 (2004) |
| c25 | | Shoji Hirano, Shusaku Tsumoto: Cluster analysis of long time-series medical datasets. Data Mining and Knowledge Discovery: Theory, Tools, and Technology 2004: 13-20 |
| c24 | | Shusaku Tsumoto, Shoji Hirano: A Comparative Study of Clustering Methods for Long Time-Series Medical Databases. MDAI 2004: 260-272 |
| c23 | | Shoji Hirano, Shusaku Tsumoto: Finding Interesting Pass Patterns from Soccer Game Records. PKDD 2004: 209-218 |
| c22 | | Shoji Hirano, Shusaku Tsumoto: On the Degree of Independence of a Contingency Matrix. Rough Sets and Current Trends in Computing 2004: 219-228 |
| c21 | | Shoji Hirano, Shusaku Tsumoto: Detection of Differences between Syntactic and Semantic Similarities. Rough Sets and Current Trends in Computing 2004: 529-538 |
| 2003 | ||
| j5 | | Shoji Hirano, Shusaku Tsumoto: An Indiscernibility-Based Clustering Method with Iterative Refinement of Equivalence Relations -Rough Clustering-. JACIII 7(2): 169-177 (2003) |
| c20 | | Shoji Hirano, Shusaku Tsumoto: Empirical Comparison of Clustering Methods for Long Time-Series Databases. Active Mining 2003: 268-286 |
| c19 | | Shusaku Tsumoto, Shoji Hirano, Eisuke Hanada: Internet-based Decision Support: Towards E-Hospital. COMPSAC 2003: 595-600 |
| c18 | | Shusaku Tsumoto, Shoji Hirano: Visualization of Rule's Similarity using Multidimensional Scaling. ICDM 2003: 339-346 |
| c17 | | Shusaku Tsumoto, Shoji Hirano: Pattern Discovery based on Rule Induction and Taxonomy Generation. ICDM 2003: 661-664 |
| c16 | | Shoji Hirano, Shusaku Tsumoto: Indiscernibility-Based Clustering: Rough Clustering. IFSA 2003: 378-386 |
| c15 | | Shoji Hirano, Shusaku Tsumoto: Empirical Evaluation of Dissimilarity Measures for Time-Series Multiscale Matching. ISMIS 2003: 454-462 |
| c14 | | Shoji Hirano, Shusaku Tsumoto: Dealing with Relative Similarity in Clustering: An Indiscernibility Based Approach. PAKDD 2003: 513-518 |
| c13 | | Shoji Hirano, Shusaku Tsumoto: An Indiscernibility-Based Clustering Method with Iterative Refinement of Equivalence Relations. PKDD 2003: 192-203 |
| 2002 | ||
| j4 | | Shusaku Tsumoto, Shoji Hirano, Akira Yasuda, Kouhei Tsumoto: Analysis of amino-acid sequences by statistical technique. Inf. Sci. 145(3-4): 205-214 (2002) |
| c12 | | Shoji Hirano, Xiaoguang Sun, Shusaku Tsumoto: On Similarity Measures for Cluster Analysis in Clinical Laboratory Examination Databases. COMPSAC 2002: 1170-1175 |
| c11 | | Shoji Hirano, Shusaku Tsumoto: Mining Similar Temporal Patterns in Long Time-Series Data and Its Application to Medicine. ICDM 2002: 219-226 |
| c10 | | Shusaku Tsumoto, Shoji Hirano, Akira Yasuda, Kouhei Tsumoto: Analysis of Amino Acid Sequences by Statistical Technique. JCIS 2002: 1169-1173 |
| c9 | | Shoji Hirano, Shusaku Tsumoto: Multiscale Comparison of Temporal Patternsin Time-Series Medical Databases. PKDD 2002: 188-199 |
| c8 | | Shoji Hirano, Shusaku Tsumoto: Segmentation of Medical Images Based on Approximations in Rough Set Theory. Rough Sets and Current Trends in Computing 2002: 554-563 |
| 2001 | ||
| j3 | | Shoji Hirano, Yutaka Hata: Fuzzy expert system for foot CT image segmentation. Image Vision Comput. 19(4): 207-216 (2001) |
| c7 | | Shoji Hirano, Shusaku Tsumoto: A Knowledge-Oriented Clustering Technique Based on Rough Sets. COMPSAC 2001: 632-637 |
| c6 | | Shoji Hirano, Xiaoguang Sun, Shusaku Tsumoto: Analysis of Time-series Medical Databases Using Multiscale Structure Matching and Rough Sets-based. FUZZ-IEEE 2001: 1547-1550 |
| c5 | | Shoji Hirano, Shusaku Tsumoto: Indiscernibility Degree of Objects for Evaluating Simplicity of Knowledge in the Clustering Procedure. ICDM 2001: 211-217 |
| c4 | | Shusaku Tsumoto, Shoji Hirano, Masahiro Inuiguchi: Workshop on Rough Set Theory and Granular Computing - Summary. JSAI Workshops 2001: 239 |
| c3 | | Shoji Hirano, Shusaku Tsumoto, Tomohiro Okuzaki, Yutaka Hata: A Clustering Method for Nominal and Numerical Data Based on Rough Set Theory. JSAI Workshops 2001: 400-405 |
| c2 | | Shoji Hirano, Tomohiro Okuzaki, Yutaka Hata, Shusaku Tsumoto, Kouhei Tsumoto: A Rough Set-Based Clustering Method with Modification of Equivalence Relations. PAKDD 2001: 507-512 |
| 2000 | ||
| j2 | | Shoji Hirano, Naotake Kamiura, Nobuyuki Matsui, Yutaka Hata: Hippocampus Extraction Based on Parallel Multiscale Structure Matching. IJPRAI 14(4): 427-439 (2000) |
| j1 | | Yutaka Hata, Syoji Kobashi, Shoji Hirano, H. Kitagaki, E. Mori: Automated segmentation of human brain MR images aided by fuzzy information granulation and fuzzy inference. IEEE Transactions on Systems, Man, and Cybernetics, Part C 30(3): 381-395 (2000) |
| 1997 | ||
| c1 | | Shoji Hirano, Naotake Kamiura, Yutaka Hata, Makoto Ishikawa: MAGNET: An Active Ditch Extraction Model. ICIP (2) 1997: 124-127 |
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