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2020 – today
- 2023
[c201]Tomohiro Kimura, Shusaku Tsumoto, Shoji Hirano:
Analysis of Medical Incident Reports using Text Mining*. IEEE Big Data 2023: 6057-6062- [c200]Hiroyuki Ikedo, Tomohiro Kimura, Shusaku Tsumoto, Shoji Hirano:
Using Hospital Information System Data to Estimate Nursing Care Needs. IEEE Big Data 2023: 6063-6068 - 2022
- [j29]Shusaku Tsumoto
, Tomohiro Kimura, Shoji Hirano:
Expectation-Maximization (EM) Clustering as a Preprocessing Method for Clinical Pathway Mining. Rev. Socionetwork Strateg. 16(1): 25-52 (2022) - [j28]Shusaku Tsumoto, Tomohiro Kimura, Shoji Hirano:
Order Trajectory Analysis for Monitoring Clinical Process. Rev. Socionetwork Strateg. 16(1): 53-70 (2022) - [c199]Tomohiro Kimura, Shusaku Tsumoto, Shoji Hirano:
Similarity Analysis of Order Trajectory for Hospital Management. IEEE Big Data 2022: 6232-6238 - [c198]Shusaku Tsumoto, Tomohiro Kimura, Shoji Hirano, Katsutoshi Yada:
Temporal Data Mining in AI-based Patient Navigation Service. IEEE Big Data 2022: 6239-6246 - 2021
- [j27]Shusaku Tsumoto, Shoji Hirano, Tomohiro Kimura, Haruko Iwata:
Mining Clinical Process from Hospital Information System: A Granular Computing Approach. Fundam. Informaticae 182(2): 181-218 (2021) - [j26]Shusaku Tsumoto, Tomohirno Kimura, Shoji Hirano:
Determination of Disease from Discharge Summaries. Rev. Socionetwork Strateg. 15(1): 49-66 (2021) - [j25]Shusaku Tsumoto, Tomohiro Kimura, Shoji Hirano:
Mining Clinical Pathways Using Dual Clustering. Rev. Socionetwork Strateg. 15(2): 287-307 (2021) - [c197]Shusaku Tsumoto, Tomohiro Kimura, Shoji Hirano:
Comparison of Clustering Strategies using a Partition Tree. IST 2021: 1-6 - 2020
- [c196]Shusaku Tsumoto, Tomohiro Kimura, Shoji Hirano:
Automated Dual Clustering for Clinical Pathway Mining*. IEEE BigData 2020: 5387-5396 - [c195]Shusaku Tsumoto, Tomohiro Kimura, Shoji Hirano:
Order Trajectory Analysis in Hospital Information System*. IEEE BigData 2020: 5397-5404 - [c194]Shusaku Tsumoto, Tomohiro Kimura, Shoji Hirano:
From Texts to Classification Knowledge. IFIP TC12 ICIS 2020: 173-184 - [c193]Shusaku Tsumoto, Tomohiro Kimura, Shoji Hirano:
Mining in Discharge Summaries. JSAI 2020: 61-72
2010 – 2019
- 2019
- [c192]Shoji Hirano, Shusaku Tsumoto:
Mining frequent temporal patterns from medical data based on fuzzy ranged relations. IEEE BigData 2019: 2654-2658 - [c191]Shusaku Tsumoto, Tomohiro Kimura, Haruko Iwata, Shoji Hirano:
Estimation of Disease Code from Electronic Patient Records. IEEE BigData 2019: 2698-2707 - [c190]Shoji Hirano, Haruko Iwata, Tomohiro Kimura, Shusaku Tsumoto:
Clinical Pathway Generation from Order Histories and Discharge Summaries. ICDM Workshops 2019: 333-340 - [c189]Shusaku Tsumoto, Shoji Hirano:
Granular Rules for Medical Diagnosis. IFSA/NAFIPS 2019: 681-691 - 2018
- [c188]Shusaku Tsumoto, Shoji Hirano, Tomohiro Kimura, Haruko Iwata:
From Hospital Big Data to Clinical Process: A Granular Computing Approach. IEEE BigData 2018: 2669-2678 - [c187]Shusaku Tsumoto, Shoji Hirano, Tomohiro Kimura, Haruko Iwata:
Construction of Clinical Pathway Generation from Nursing Records and Discharge Summaries. ICDM Workshops 2018: 470-477 - [c186]Shusaku Tsumoto, Tomohiro Kimura, Haruko Iwata, Shoji Hirano:
Empirical Comparison of Distances for Agglomerative Hierarchical Clustering. IPMU (2) 2018: 538-548 - [c185]Shusaku Tsumoto, Tomohiro Kimura, Haruko Iwata, Shoji Hirano:
Clinical Pathway Generation from Hospital Information System. ITQM 2018: 545-553 - [c184]Shusaku Tsumoto, Shoji Hirano, Tomohiro Kimura, Haruko Iwata:
Clinical Pathway Generation Based on Hierarchical Clustering and EM Clustering. SMC 2018: 1327-1332 - [c183]Shusaku Tsumoto, Shoji Hirano, Tomohiro Kimura, Haruko Iwata:
Empirical Comparison of Similarities for Agglomerative Hierarchical Clustering. SMC 2018: 3405-3410 - 2017
- [c182]Shusaku Tsumoto, Tomohiro Kimura, Haruko Iwata, Shoji Hirano:
Construction of discharge summaries classifier. IEEE ICCI*CC 2017: 513-519 - [c181]Shusaku Tsumoto, Tomohiro Kimura, Haruko Iwata, Shoji Hirano:
Mining text for disease diagnosis in hospital information system. IEEE BigData 2017: 1850-1859 - [c180]Shoji Hirano, Shusaku Tsumoto:
Frequent Temporal Pattern Mining for Medical Data Based on Ranged Relations. ICDM Workshops 2017: 612-616 - [c179]Shusaku Tsumoto, Tomohiro Kimura, Haruko Iwata, Shoji Hirano:
Construction of Discharge Summaries Classifier. ICHI 2017: 74-82 - [c178]Shusaku Tsumoto, Tomohiro Kimura, Haruko Iwata, Shoji Hirano:
Discharge Summaries Classifier. IIH-MSP (2) 2017: 352-360 - [c177]Shusaku Tsumoto, Tomohiro Kimura, Haruko Iwata, Shoji Hirano:
Mining Text for Disease Diagnosis. ITQM 2017: 1133-1140 - [c176]Shusaku Tsumoto, Shoji Hirano:
Induction of Rule for Differential Diagnosis. IJCRS (1) 2017: 350-361 - 2016
- [j24]Shusaku Tsumoto, Shoji Hirano:
Multidimensional temporal mining in hospital information system. Int. J. Comput. Intell. Stud. 5(3/4): 317-337 (2016) - [c175]Shusaku Tsumoto, Shoji Hirano:
Active mining process for software quality estimation. ICCI*CC 2016: 268-274 - [c174]Shusaku Tsumoto, Shoji Hirano:
Construction of linguistic variables based on rule induction and concept hierarchy. ICCI*CC 2016: 516-522 - [c173]Shusaku Tsumoto, Shoji Hirano, Haruko Iwata:
Construction of clinical pathway from histories of clinical actions in hospital information system. IEEE BigData 2016: 1972-1981 - [c172]Shusaku Tsumoto, Shoji Hirano, Haruko Iwata, Norio Yoshimoto, Tomohiro Kimura:
Mining process for improvement of clinical process quality. IEEE BigData 2016: 1982-1990 - [c171]Shusaku Tsumoto, Shoji Hirano:
Incremental Updates of Rough Set-Based Probabilistic Rules. CMCSN 2016: 28-31 - [c170]Shoji Hirano:
Temporal Data Mining on the Stay Time of Outpatients and Treatment Processes. ICDM Workshops 2016: 527-530 - [c169]Haruko Iwata, Shusaku Tsumoto, Shoji Hirano:
Dual Clustering for Clinical Care Construction. ICHI 2016: 314 - [c168]Shusaku Tsumoto, Shoji Hirano:
On Behavior of Statistical Indices in Incremental Context. IJCRS 2016: 483-492 - [c167]Shusaku Tsumoto, Shoji Hirano:
Linguistic Variables Construction in Information Table. IJCRS 2016: 493-502 - [c166]Shusaku Tsumoto, Shoji Hirano:
Construction of linguistic variables from data and domain knowledge. SMC 2016: 4519-4524 - 2015
- [j23]Haruko Iwata, Shoji Hirano, Shusaku Tsumoto:
Maintenance and Discovery of Domain Knowledge for Nursing Care using Data in Hospital Information System. Fundam. Informaticae 137(2): 237-252 (2015) - [c165]Shusaku Tsumoto, Shoji Hirano:
Mining probabilistic rules using nonmonotonic rule layers. ICCI*CC 2015: 184-191 - [c164]Shusaku Tsumoto, Shoji Hirano:
Analytics for Hospital Management. ASE BD&SI 2015: 15:1-15:6 - [c163]Shusaku Tsumoto, Shoji Hirano, Haruko Iwata:
Dual Clustering and Data Decomposition for Nursing Care Management. ASE BD&SI 2015: 24:1-24:6 - [c162]Shusaku Tsumoto, Shoji Hirano, Haruko Iwata:
Data decomposition and dual clustering for clinical care management. IEEE BigData 2015: 1475-1584 - [c161]Shusaku Tsumoto, Shoji Hirano:
Granular formalization of medical diagnostic process. IEEE BigData 2015: 1608-1614 - [c160]Shusaku Tsumoto, Shoji Hirano:
Rule Mining Based on Nonmonotonic Rule Layers and Its Application to Medicine. ICDM Workshops 2015: 365-372 - [c159]Shusaku Tsumoto, Shoji Hirano, Toshihiko Kawamura:
Statistical Estimation of Software Quality in Hospital Information System. ICServ 2015: 341-350 - [c158]Shusaku Tsumoto, Shoji Hirano, Haruko Iwata:
Mining Schedule of Nursing Care Based on Dual-Clustering. ITQM 2015: 1203-1212 - [c157]Shusaku Tsumoto, Shoji Hirano:
Layered Rule Induction. ITQM 2015: 1213-1220 - [c156]Shusaku Tsumoto, Shoji Hirano:
Formalization of Medical Diagnostic Rules. RSFDGrC 2015: 24-35 - 2014
- [j22]Shusaku Tsumoto, Haruko Iwata, Shoji Hirano, Yuko Tsumoto:
Similarity-based behavior and process mining of medical practices. Future Gener. Comput. Syst. 33: 21-31 (2014) - [c155]Shusaku Tsumoto, Shoji Hirano:
Incremental rule induction based on updates of statistical indices. ICCI*CC 2014: 408-415 - [c154]Shusaku Tsumoto, Shoji Hirano:
Formal analysis of cross-validation for rule induction using probabilistic indices. ICCI*CC 2014: 416-423 - [c153]Shusaku Tsumoto, Shoji Hirano:
Formal analysis of cross-validation based on decremental sampling scheme. GrC 2014: 298-303 - [c152]Shusaku Tsumoto, Shoji Hirano:
Probabilistic rule induction based on incremental sampling scheme. GrC 2014: 304-309 - [c151]Shusaku Tsumoto, Shoji Hirano:
Healthcare IT: Integration of consumer healthcare data and electronic medical records for chronic disease management. GrC 2014: 310-315 - [c150]Shoji Hirano, Shusaku Tsumoto:
Visualization of Patient Distributions in a Hospital Based on the Clinical Actions Stored in EHR. ICDM Workshops 2014: 284-288 - [c149]Haruko Iwata, Shoji Hirano, Shusaku Tsumoto:
Construction of Clinical Pathway based on Similarity-based Mining in Hospital Information System. ITQM 2014: 1107-1115 - [c148]Shoji Hirano, Shusaku Tsumoto:
Mining Typical Order Sequences from EHR for Building Clinical Pathways. PAKDD Workshops 2014: 39-49 - [c147]Shusaku Tsumoto, Shoji Hirano:
Evaluation of Leave-One Out Method Based on Incremental Sampling Scheme. RSEISP 2014: 225-236 - [c146]Shoji Hirano, Shusaku Tsumoto:
Visualizing dynamics of patients in hospitals using devise locations. SMC 2014: 2547-2550 - [c145]Shusaku Tsumoto, Shoji Hirano:
Formal analysis of leave-one out method based on decremental sampling scheme. SMC 2014: 2780-2785 - [c144]Shusaku Tsumoto, Shoji Hirano:
Homological analysis of statistical dependence. SMC 2014: 2786-2791 - [c143]Shusaku Tsumoto, Shoji Hirano, Haruko Iwata:
Towards Data-Oriented Schedule Management in Hospital. SRII Global Conference 2014: 181-190 - [c142]Shusaku Tsumoto, Shoji Hirano:
Formal Analysis of Leave-One-Out Methods Based on Decremental Sampling Scheme. WI-IAT (1) 2014: 371-378 - [c141]Shusaku Tsumoto, Shoji Hirano:
Formal Analysis of Statistical Dependence Based Homological Algebra. WI-IAT (1) 2014: 379-385 - 2013
- [j21]Shusaku Tsumoto, Shoji Hirano:
Incremental Induction of Medical Diagnostic Rules Based on Incremental Sampling Scheme and SubRule Layers. Fundam. Informaticae 127(1-4): 209-223 (2013) - [j20]Shusaku Tsumoto, Shoji Hirano:
Combinatorics of Information Granule in Contingency Table. Int. J. Intell. Syst. 28(9): 892-906 (2013) - [j19]Shusaku Tsumoto, Shoji Hirano:
Combinatorics in Pearson residuals. Int. J. Knowl. Eng. Soft Data Paradigms 4(1): 72-84 (2013) - [j18]Shoji Hirano, Shusaku Tsumoto:
Clustering of non-metric proximity data based on bi-links with ϵ-indiscernibility. J. Intell. Inf. Syst. 41(1): 61-71 (2013) - [c140]Shusaku Tsumoto, Shoji Hirano, Haruko Iwata:
Granularity-based mining for construction of nursing care plan. ICCI*CC 2013: 282-291 - [c139]Shusaku Tsumoto, Shoji Hirano, Haruko Iwata:
Mining nursing care plan from data extracted from hospital information system. ASONAM 2013: 956-961 - [c138]Shoji Hirano, Shusaku Tsumoto:
Cluster analysis of treatment processes based on the typicalness measure for building clinical pathways. BIBM 2013: 31-32 - [c137]Shusaku Tsumoto, Shoji Hirano, Haruko Iwata:
Granularity-based temporal data mining in hospital information system. IEEE BigData 2013: 32-40 - [c136]Haruko Iwata, Shoji Hirano, Shusaku Tsumoto:
Mining Clinical Pathway Based on Clustering and Feature Selection. Brain and Health Informatics 2013: 237-245 - [c135]Shusaku Tsumoto, Shoji Hirano:
Incremental Induction of Medical Diagnostic Rules. Brain and Health Informatics 2013: 409-417 - [c134]Haruko Iwata, Shusaku Tsumoto, Shoji Hirano:
Clinical schedule management based on granularity-based mining. CYBCONF 2013: 237-242 - [c133]Shusaku Tsumoto, Shoji Hirano:
Evaluation of set-based indices based on incremental sampling framework. FUZZ-IEEE 2013: 1-8 - [c132]Shusaku Tsumoto, Shoji Hirano:
Algebraic analysis of statistical dependence. GrC 2013: 303-308 - [c131]Shusaku Tsumoto, Shoji Hirano:
Incremental induction of medical diagnostic rules. GrC 2013: 309-314 - [c130]Haruko Iwata, Shusaku Tsumoto, Shoji Hirano:
Data mining based clinical care plan construction. iCAST/UMEDIA 2013: 286-292 - [c129]Shoji Hirano, Shusaku Tsumoto:
Clustering of Order Sequences Based on the Typicalness Index for Finding Clinical Pathway Candidates. ICDM Workshops 2013: 206-210 - [c128]Haruko Iwata, Shusaku Tsumoto, Shoji Hirano:
Clinical Schedule Management Using Similarity-Based Mining Methods. ICHI 2013: 396-405 - [c127]Shusaku Tsumoto, Shoji Hirano, Haruko Iwata:
Data-Oriented Maintenance of Schedule Management of Nursing Care. ICServ 2013: 169-177 - [c126]Shusaku Tsumoto, Shoji Hirano:
Evaluation of Incremental Change of Set-Based Indices. RSKT 2013: 188-199 - [c125]Shusaku Tsumoto, Shoji Hirano:
Incremental Induction of Probabilistic Rules Based on Incremental Sampling Scheme. SMC 2013: 812-817 - [c124]Shoji Hirano, Shusaku Tsumoto:
Mining Clinical Pathway Candidates from Order History Based on the Clustering of Order Sequences. SMC 2013: 3425-3429 - [c123]Shusaku Tsumoto, Shoji Hirano, Haruko Iwata:
Mining Clinical Pathway Using Clustering and Rule Induction. SMC 2013: 4860-4865 - 2012
- [c122]Shusaku Tsumoto, Haruko Iwata, Shoji Hirano, Yuko Tsumoto:
Exploratory temporal data mining process in hospital information systems. ICCI*CC 2012: 145-152 - [c121]Shusaku Tsumoto, Shoji Hirano, Haruko Iwata:
Temporal data mining of order entry histories for characterization of medical practice. CBMS 2012: 1-4 - [c120]Shusaku Tsumoto, Haruko Iwata, Shoji Hirano:
Construction and maintenance of clinical pathways using data mining methods. MIX-HS 2012: 47-52 - [c119]Shusaku Tsumoto, Shoji Hirano:
Degree of freedom and numbers of subdeterminants in contingency table. GrC 2012: 481-486 - [c118]Shusaku Tsumoto, Shoji Hirano:
Geometrical interpretation of pearson residuals. GrC 2012: 487-492 - [c117]Shusaku Tsumoto, Shoji Hirano, Yuko Tsumoto:
Visualization of doctors' behavior using similarity-based methods. GrC 2012: 767-770 - [c116]Shusaku Tsumoto, Shoji Hirano, Haruko Iwata:
Temporal Data Mining for Nursing Schedule Management. IBICA 2012: 229-234 - [c115]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 - [c114]Shusaku Tsumoto, Shoji Hirano:
Multidimensional temporal mining in clinical data. IHI 2012: 563-572 - [c113]Shusaku Tsumoto, Shoji Hirano:
Incremental Rules Induction Method Based on Three Rule Layers. ISMIS 2012: 71-80 - [c112]Shusaku Tsumoto, Shoji Hirano:
Incremental Rules Induction Based on Rule Layers. RSKT 2012: 139-148 - [c111]Shusaku Tsumoto, Shoji Hirano:
Trajectories mining in hospital information systems. SMC 2012: 389-394 - [c110]Shusaku Tsumoto, Shoji Hirano:
Information granules in medical differential diagnosis. SMC 2012: 395-401 - [c109]Shusaku Tsumoto, Shoji Hirano, Haruko Iwata:
Data-oriented maintenance of clinical pathway using clustering and multidimensional scaling. SMC 2012: 2596-2600 - [c108]Shusaku Tsumoto, Shoji Hirano, Haruko Iwata, Yuko Tsumoto:
Characterizing Hospital Services Using Temporal Data Mining. SRII Global Conference 2012: 219-230 - 2011
- [j17]Shusaku Tsumoto, Shoji Hirano:
Residual as Linear Sum of Matrix Determinants in Multiway Contingency Tables. Int. J. Comput. Intell. Syst. 4(5): 1080-1089 (2011) - [j16]Shusaku Tsumoto, Shoji Hirano:
Detection of risk factors using trajectory mining. J. Intell. Inf. Syst. 36(3): 403-425 (2011) - [c107]Shusaku Tsumoto, Shoji Hirano, Haruko Iwata, Yuko Tsumoto:
Capturing Behavior of Medical Staff: A Similarity-Oriented Temporal Data Mining Approach. FGIT 2011: 1-16 - [c106]Shoji Hirano, Shusaku Tsumoto:
A clustering method for asymmetric proximity data based on bi-links with ε-indiscernibility. GrC 2011: 242-245 - [c105]Shusaku Tsumoto, Shoji Hirano, Yuko Tsumoto:
Clustering-based analysis in hospital information systems. GrC 2011: 669-674 - [c104]Shusaku Tsumoto, Shoji Hirano:
Combinatorics of pearson residuals and degree of freedom in contingency tables. GrC 2011: 675-680 - [c103]Shusaku Tsumoto, Shoji Hirano, Yuko Tsumoto:
Visualization of Hospital Services Using Data Mining Methods. ICDM Workshops 2011: 1183-1190 - [c102]Shusaku Tsumoto, Shoji Hirano, Yuko Tsumoto:
Information reuse in hospital information systems: A data mining approach. IRI 2011: 172-176 - [c101]Shusaku Tsumoto, Shoji Hirano:
Information Reuse in Hospital Information Systems: A Similarity-Oriented Data Mining Approach. RSKT 2011: 382-387 - [c100]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. Informaticae 98(1): 107-121 (2010) - [j14]Shoji Hirano, Shusaku Tsumoto:
Multiscale Comparison and Clustering of Three-Dimensional Trajectories Based on Curvature Maxima. Int. J. Inf. Technol. Decis. Mak. 9(6): 889-904 (2010) - [c99]Shusaku Tsumoto, Shoji Hirano, Hidenao Abe:
Sampling from databases for rule induction methods based on likelihood ratio test. IEEE ICCI 2010: 174-179 - [c98]Shoji Hirano, Shusaku Tsumoto:
Hierarchical, Granular Representation of Non-metric Proximity Data. GrC 2010: 217-222 - [c97]Shusaku Tsumoto, Shoji Hirano:
Information Granules of Statistical Dependence in Multiway Contingency Tables. GrC 2010: 483-488 - [c96]Shusaku Tsumoto, Shoji Hirano:
Geometrical and Combinatorial Nature of Pearson Residuals. GrC 2010: 489-494 - [c95]Shoji Hirano, Shusaku Tsumoto:
Curvature Maxima-based Trajectories Mining. ICDM Workshops 2010: 257-264 - [c94]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 - [c93]Shusaku Tsumoto, Shoji Hirano, Yuko Tsumoto:
Towards Data-Oriented Hospital Services: Data Mining-Based Hospital Management. ICDM Workshops 2010: 1076-1083 - [c92]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 - [c91]Shoji Hirano, Shusaku Tsumoto:
Representation of Granularity for Non-Euclidian Relational Data by Jaccard Coefficients and Binary Classifications. RSCTC 2010: 721-729 - [c90]Shusaku Tsumoto, Shoji Hirano, Hidenao Abe:
Likelihood-Based Sampling from Databases for Rule Induction Methods. RSKT 2010: 265-272 - [c89]Shusaku Tsumoto, Shoji Hirano:
Residual Analysis of Statistical Dependence in Multiway Contingency Tables. RSKT 2010: 273-280 - [c88]Shoji Hirano, Shusaku Tsumoto:
Multiscale Comparison of Three-Dimensional Trajectories Based on the Curvature Maxima and Its Application to Medicine. SBP 2010: 128-137 - [c87]Shusaku Tsumoto, Shoji Hirano:
Three dimensional trajectories mining. SMC 2010: 500-505
2000 – 2009
- 2009
- [j13]Shusaku Tsumoto, Shoji Hirano:
Statistical Independence and Determinants in a Contingency Table - Interpretation of Pearson Residuals based on Linear Algebra -. Fundam. Informaticae 90(3): 251-267 (2009) - [j12]Shusaku Tsumoto, Shoji Hirano:
Contingency Matrix Theory II: Degree of Dependence as Granularity. Fundam. Informaticae 90(4): 427-442 (2009) - [c86]Shusaku Tsumoto, Shoji Hirano:
Temporal data mining for hospital management. Data Mining, Intrusion Detection, Information Security and Assurance, and Data Networks Security 2009: 73440A - [c85]Shusaku Tsumoto, Shoji Hirano, Hidenao Abe:
Multivariate statistical independence and contingency tables. GrC 2009: 544-548 - [c84]Shoji Hirano, Shusaku Tsumoto:
Multiscale Comparison of Three-Dimensional Trajectories: A Preliminary Step. RSFDGrC 2009: 361-368 - [c83]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. Trans. Comput. Sci. 2: 161-179 (2008) - [c82]Shusaku Tsumoto, Shoji Hirano:
Fuzziness from attribute generalization in information table. IEEE ICCI 2008: 455-461 - [c81]Shusaku Tsumoto, Shoji Hirano:
Statistical independence in three-variables contingency cube. IEEE ICCI 2008: 468-474 - [c80]Shusaku Tsumoto, Shoji Hirano:
Mining Trajectories of Laboratory Data using Multiscale Matching and Clustering. CBMS 2008: 626-631 - [c79]Shusaku Tsumoto, Shoji Hirano:
Partial statistical independence in contingency matrix. FUZZ-IEEE 2008: 2412-2419 - [c78]Shoji Hirano, Shusaku Tsumoto:
Trajectory mining using multiscale matching and clustering. FUZZ-IEEE 2008: 2420-2427 - [c77]Shusaku Tsumoto, Shoji Hirano:
Decomposition of Pearson Residuals of Three-variables Contingency Cube. GrC 2008: 61-66 - [c76]Shoji Hirano, Shusaku Tsumoto:
Hierarchical Clustering of Asymmetric Proximity Data based on the Indiscernibility-level. GrC 2008: 275-280 - [c75]Shusaku Tsumoto, Shoji Hirano:
Statistical Independence and Contingency Matrix. ICDM Workshops 2008: 643-648 - [c74]Shusaku Tsumoto, Shoji Hirano:
Hospital Management Based on Data Mining. ISDA (3) 2008: 257-262 - [c73]Shoji Hirano, Shusaku Tsumoto:
Detection of Risk Factors as Temporal Data Mining. PAKDD Workshops 2008: 143-156 - [c72]Shusaku Tsumoto, Shoji Hirano:
Statistical Independence of Multi-variables from the Viewpoint of Linear Algebra. RSCTC 2008: 103-112 - [c71]Shoji Hirano, Shusaku Tsumoto:
Hierarchical Clustering of Non-Euclidean Relational Data Using Indiscernibility-Level. RSKT 2008: 332-339 - [c70]Shusaku Tsumoto, Shoji Hirano:
Statistical dependence in contingency data cube. SMC 2008: 2759-2764 - [p2]Shusaku Tsumoto, Shoji Hirano:
Risk Mining as New Trends in Hospital Management. Next Generation of Data Mining 2008 - [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. Informaticae 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. Int. J. Knowl. Based Intell. Eng. Syst. 11(5): 345-354 (2007) - [c69]Shusaku Tsumoto, Shoji Hirano:
Charcteristics of Pearson Residuals in a Contingency Matrix. IEEE ICCI 2007: 195-204 - [c68]Shoji Hirano, Shusaku Tsumoto:
Cluster Analysis of Trajectory Data on Hospital Laboratory Examinations. AMIA 2007 - [c67]Shoji Hirano, Shusaku Tsumoto:
Cluster analysis of temporal trajectories of hospital laboratory examinations. Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2007: 65700E - [c66]Shoji Hirano, Shusaku Tsumoto:
Discovery of exacerbating cases in chronic hepatitis based on cluster analysis of time-series platelet count data. Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2007: 65700F - [c65]Shoji Hirano, Shusaku Tsumoto:
Trajectory Analysis of Laboratory Tests as Medical Complex Data Mining. MCD 2007: 27-41 - [c64]Shusaku Tsumoto, Shoji Hirano:
Meaning of Pearson Residuals - Linear Algebra View. GrC 2007: 465-470 - [c63]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 - [c62]Shoji Hirano, Shusaku Tsumoto:
Discovery of Risky Cases in Chronic Diseases: An Approach Using Trajectory Grouping. JSAI 2007: 289-302 - [c61]Shusaku Tsumoto, Shoji Hirano:
Visualization of Similarities and Dissimilarities Between Rules Using Multidimensional Scaling. KES (2) 2007: 978-986 - [c60]Shoji Hirano, Shusaku Tsumoto:
Dealing with granularity on non-euclidean relational data based on indiscernibility level. SMC 2007: 3772-3777 - [c59]Shusaku Tsumoto, Shoji Hirano:
Contingency matrix theory. SMC 2007: 3778-3783 - 2006
- [c58]Shusaku Tsumoto, Shoji Hirano:
Decomposition of Contingency Table as Tensor Product. FUZZ-IEEE 2006: 369-376 - [c57]Shusaku Tsumoto, Shoji Hirano:
Analysis of sample size effect on dependency of contingency matrix. GrC 2006: 712-715 - [c56]Shusaku Tsumoto, Shoji Hirano:
Characterization of contextual independence of contingency matrix. GrC 2006: 716-719 - [c55]Shusaku Tsumoto, Shoji Hirano:
Residual Matrix and Statistical Independence in a Contingency Table. ICDM Workshops 2006: 433-437 - [c54]Shoji Hirano, Shusaku Tsumoto:
Cluster Analysis of Time-Series Medical Data Based on the Trajectory Representation and Multiscale Comparison Techniques. ICDM 2006: 896-901 - [c53]Shoji Hirano, Shusaku Tsumoto:
Characteristics of Indiscernibility Degree in Rough Clustering Examined Using Perfect Initial Equivalence Relations. ISMIS 2006: 454-462 - [c52]Shusaku Tsumoto, Shoji Hirano:
Distribution of Determinants of Contingency Matrix. RSCTC 2006: 567-576 - [c51]Shusaku Tsumoto, Shoji Hirano:
Interpretation of Contingency Matrix Using Marginal Distributions. RSCTC 2006: 577-586 - [c50]Shoji Hirano, Shusaku Tsumoto:
A Framework for Unsupervised Selection of Indiscernibility Threshold in Rough Clustering. RSCTC 2006: 872-881 - [c49]Shoji Hirano, Shusaku Tsumoto:
On the Nature of Degree of Indiscerniblity for Rough Clustering. SMC 2006: 3447-3452 - [c48]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:
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 [contents] - 2005
- [j8]Shoji Hirano, Shusaku Tsumoto:
Rough representation of a region of interest in medical images. Int. J. Approx. Reason. 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) - [c47]Shoji Hirano, Shusaku Tsumoto:
Classification of temporal sequences using multiscale matching and rough clustering. Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2005: 202-213 - [c46]Shusaku Tsumoto, Shoji Hirano:
On statistical independence of a contingency matrix. Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2005: 291-302 - [c45]Shusaku Tsumoto, Shoji Hirano:
Degree of Dependence as Granularity in a Contingency Table. GrC 2005: 63-69 - [c44]Shoji Hirano, Shusaku Tsumoto:
An indiscernibility-based clustering method. GrC 2005: 468-473 - [c43]Shusaku Tsumoto, Shoji Hirano:
Linear independence in a contingency table. GrC 2005: 646-651 - [c42]Shoji Hirano, Shusaku Tsumoto:
Grouping of Soccer Game Records by Multiscale Comparison Technique and Rough Clustering. HIS 2005: 399-404 - [c41]Shusaku Tsumoto, Shoji Hirano:
Visualization of Similarities and Dissimilarities in Rules Using Multidimensional Scaling. ISMIS 2005: 38-46 - [c40]Shoji Hirano, Shusaku Tsumoto:
Clustering Time-Series Medical Databases Based on the Improved Multiscale Matching. ISMIS 2005: 612-621 - [c39]Shoji Hirano, Shusaku Tsumoto:
On Constructing Clusters from Non-Euclidean Dissimilarity Matrix by Using Rough Clustering. JSAI Workshops 2005: 5-16 - [c38]Shusaku Tsumoto, Shoji Hirano:
On Degree of Dependence Based on Contingency Matrix. RSFDGrC (1) 2005: 471-480 - [c37]Shoji Hirano, Shusaku Tsumoto:
A Clustering Method for Spatio-temporal Data and Its Application to Soccer Game Records. RSFDGrC (1) 2005: 612-621 - [c36]Shoji Hirano, Shusaku Tsumoto:
A Parallel, Structural Comparison Scheme of Time-Series Implemented on a PC Cluster. SAINT Workshops 2005: 344-347 - [c35]Shoji Hirano, Shusaku Tsumoto:
Strucutural Comparison and Cluster Analysis of Time-Series Medical Data. SMC 2005: 1506-1511 - [c34]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) - [c33]Shoji Hirano, Shusaku Tsumoto:
Cluster analysis of long time-series medical datasets. Data Mining and Knowledge Discovery: Theory, Tools, and Technology 2004: 13-20 - [c32]Shusaku Tsumoto, Shoji Hirano:
A Comparative Study of Clustering Methods for Long Time-Series Medical Databases. MDAI 2004: 260-272 - [c31]Shoji Hirano, Shusaku Tsumoto:
Finding Interesting Pass Patterns from Soccer Game Records. PKDD 2004: 209-218 - [c30]Shoji Hirano, Shusaku Tsumoto:
On the Degree of Independence of a Contingency Matrix. Rough Sets and Current Trends in Computing 2004: 219-228 - [c29]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-. J. Adv. Comput. Intell. Intell. Informatics 7(2): 169-177 (2003) - [c28]Shoji Hirano, Shusaku Tsumoto:
Multiscale Analysis of Long Time-series Medical Databases. AMIA 2003 - [c27]Shoji Hirano, Shusaku Tsumoto:
Empirical Comparison of Clustering Methods for Long Time-Series Databases. Active Mining 2003: 268-286 - [c26]Shusaku Tsumoto, Shoji Hirano, Eisuke Hanada:
Internet-based Decision Support: Towards E-Hospital. COMPSAC 2003: 595-600 - [c25]Shoji Hirano, Shusaku Tsumoto:
Comparison of similarity measures and clustering methods for time-series medical data mining. Data Mining and Knowledge Discovery: Theory, Tools, and Technology 2003: 219-225 - [c24]Shusaku Tsumoto, Shoji Hirano:
Visualization of Rule's Similarity using Multidimensional Scaling. ICDM 2003: 339-346 - [c23]Shusaku Tsumoto, Shoji Hirano:
Pattern Discovery based on Rule Induction and Taxonomy Generation. ICDM 2003: 661-664 - [c22]Shoji Hirano, Shusaku Tsumoto:
Indiscernibility-Based Clustering: Rough Clustering. IFSA 2003: 378-386 - [c21]Shoji Hirano, Shusaku Tsumoto:
Empirical Evaluation of Dissimilarity Measures for Time-Series Multiscale Matching. ISMIS 2003: 454-462 - [c20]Shoji Hirano, Shusaku Tsumoto:
Dealing with Relative Similarity in Clustering: An Indiscernibility Based Approach. PAKDD 2003: 513-518 - [c19]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) - [c18]Shoji Hirano, Shusaku Tsumoto:
Mining Interesting Patterns in Time-series Medical Databases: A Hybrid Approach of Multiscale Matching and Rough Clustering. AMIA 2002 - [c17]Shoji Hirano, Xiaoguang Sun, Shusaku Tsumoto:
On Similarity Measures for Cluster Analysis in Clinical Laboratory Examination Databases. COMPSAC 2002: 1170-1175 - [c16]Xiaoguang Sun, Shoji Hirano, Shusaku Tsumoto:
Evaluation of similarity measures for analysis of databases on laboratory examinations. Data Mining and Knowledge Discovery: Theory, Tools, and Technology 2002: 324-333 - [c15]Shoji Hirano, Xiaoguang Sun, Shusaku Tsumoto:
Dealing with multiple types of expert knowledge in medical image segmentation: a rough sets style approach. FUZZ-IEEE 2002: 884-889 - [c14]Shoji Hirano, Shusaku Tsumoto:
Mining Similar Temporal Patterns in Long Time-Series Data and Its Application to Medicine. ICDM 2002: 219-226 - [c13]Shusaku Tsumoto, Shoji Hirano, Akira Yasuda, Kouhei Tsumoto:
Analysis of Amino Acid Sequences by Statistical Technique. JCIS 2002: 1169-1173 - [c12]Shoji Hirano, Shusaku Tsumoto:
Multiscale Comparison of Temporal Patternsin Time-Series Medical Databases. PKDD 2002: 188-199 - [c11]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 Vis. Comput. 19(4): 207-216 (2001) - [c10]Shoji Hirano, Shusaku Tsumoto:
A Knowledge-Oriented Clustering Technique Based on Rough Sets. COMPSAC 2001: 632-637 - [c9]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 - [c8]Shoji Hirano, Shusaku Tsumoto:
Indiscernibility Degree of Objects for Evaluating Simplicity of Knowledge in the Clustering Procedure. ICDM 2001: 211-217 - [c7]Shusaku Tsumoto, Shoji Hirano, Masahiro Inuiguchi:
Workshop on Rough Set Theory and Granular Computing - Summary. JSAI Workshops 2001: 239 - [c6]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 - [c5]Shoji Hirano, Shusaku Tsumoto, Tomohiro Okuzaki, Yutaka Hata:
A Clustering Method Based on Rough Sets and Its Application to Knowledge Discovery in the Medical Database. MedInfo 2001: 206-210 - [c4]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. Int. J. Pattern Recognit. Artif. Intell. 14(4): 427-439 (2000) - [j1]Yutaka Hata, Syoji Kobashi, Shoji Hirano, Hajime Kitagaki, Etsuro Mori:
Automated segmentation of human brain MR images aided by fuzzy information granulation and fuzzy inference. IEEE Trans. Syst. Man Cybern. Part C 30(3): 381-395 (2000) - [c3]Shoji Hirano, Yutaka Hata, Nobuyuki Matsui, Yoshiro Ando, Makato Ishikawa:
Segmentation of the fractured foot CT image: a fuzzy-rule-based approach. Medical Imaging: Image Processing 2000
1990 – 1999
- 1998
- [c2]Yutaka Hata, Syoji Kobashi, Shoji Hirano:
Medical image segmentation by fuzzy logic techniques. SMC 1998: 4098-4103 - 1997
- [c1]Shoji Hirano, Naotake Kamiura, Yutaka Hata, Makoto Ishikawa:
MAGNET: An Active Ditch Extraction Model. ICIP (2) 1997: 124-127
Coauthor Index
[c201] [c200] [j29] [j28] [c199] [c198] [j27] [j26] [j25] [c197] [c196] [c195] [c194] [c193] [c192] [c191] [c190] [c189] [c188] [c187] [c186] [c185] [c184] [c183] [c182] [c181] [c180] [c179] [c178] [c177] [c176] [j24] [c175] [c174] [c173] [c172] [c171] [c169] [c168] [c167] [c166] [j23] [c165] [c164] [c163] [c162] [c161] [c160] [c159] [c158] [c157] [c156] [j22] [c155] [c154] [c153] [c152] [c151] [c150] [c149] [c148] [c147] [c146] [c145] [c144] [c143] [c142] [c141] [j21] [j20] [j19] [j18] [c140] [c139] [c138] [c137] [c136] [c135] [c134] [c133] [c132] [c131] [c130] [c129] [c128] [c127] [c126] [c125] [c124] [c123] [c122] [c121] [c120] [c119] [c118] [c117] [c116] [c115] [c114] [c113] [c112] [c111] [c110] [c109] [c108] [j17] [j16] [c107] [c106] [c105] [c104] [c103] [c102] [c101] [c100] [j15] [j14] [c99] [c98] [c97] [c96] [c95] [c94] [c93] [c92] [c91] [c90] [c89] [c88] [c87] [j13] [j12] [c86] [c85] [c84] [c83] [r1] [j11] [c82] [c81] [c80] [c79] [c78] [c77] [c76] [c75] [c74] [c73] [c72] [c71] [c70] [p2] [p1] [j10] [j9] [c69] [c68] [c67] [c66] [c65] [c64] [c63] [c62] [c61] [c60] [c59] [c58] [c57] [c56] [c55] [c54] [c53] [c52] [c51] [c50] [c49] [c48] [j8] [j7] [c47] [c46] [c45] [c44] [c43] [c42] [c41] [c40] [c39] [c38] [c37] [c36] [c35] [c34] [j6] [c33] [c32] [c31] [c30] [c29] [j5] [c28] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [j4] [c18] [c17] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [c9] [c8] [c7] [c6] [c5] [c4]
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