2009 | ||
---|---|---|
191 | Djamel A. Zighed, Shusaku Tsumoto, Zbigniew W. Ras, Hakim Hacid: Mining Complex Data Springer 2009 | |
190 | EE | Sanjay Chawla, Takashi Washio, Shin-ichi Minato, Shusaku Tsumoto, Takashi Onoda, Seiji Yamada, Akihiro Inokuchi: New Frontiers in Applied Data Mining, PAKDD 2008 International Workshops, Osaka, Japan, May 20-23, 2008. Revised Selected Papers Springer 2009 |
189 | EE | Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating Learning Algorithms Composed by a Constructive Meta-learning Scheme for a Rule Evaluation Support Method. Mining Complex Data 2009: 95-111 |
188 | EE | Yingxu Wang, Du Zhang, Shusaku Tsumoto: Preface: Cognitive Informatics, Cognitive Computing, and Their Denotational Mathematical Foundations (I). Fundam. Inform. 90(3): (2009) |
187 | EE | 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) |
186 | EE | Hidenao Abe, Shusaku Tsumoto: Investigating Accuracies of Classifications for Randomized Imbalanced Class Distributions. Fundam. Inform. 90(4): 369-378 (2009) |
185 | EE | Shusaku Tsumoto, Shoji Hirano: Contingency Matrix Theory II: Degree of Dependence as Granularity. Fundam. Inform. 90(4): 427-442 (2009) |
184 | EE | Yingxu Wang, Du Zhang, Shusaku Tsumoto: Preface: Cognitive Informatics, Cognitive Computing, and Their Denotational Mathematical Foundations (II). Fundam. Inform. 90(4): (2009) |
2008 | ||
183 | Zbigniew W. Ras, Shusaku Tsumoto, Djamel A. Zighed: Mining Complex Data, ECML/PKDD 2007 Third International Workshop, MCD 2007, Warsaw, Poland, September 17-21, 2007, Revised Selected Papers MCD 2008 | |
182 | EE | Shuichi Iwata, Yukio Ohsawa, Shusaku Tsumoto, Ning Zhong, Yong Shi, Lorenzo Magnani: Communications and Discoveries from Multidisciplinary Data Springer 2008 |
181 | EE | Shusaku Tsumoto, Shoji Hirano: Mining Trajectories of Laboratory Data using Multiscale Matching and Clustering. CBMS 2008: 626-631 |
180 | EE | Hidenao Abe, Shusaku Tsumoto: Comparing Accuracies of Rule Evaluation Models to Determine Human Criteria on Evaluated Rule Sets. ICDM Workshops 2008: 1-7 |
179 | EE | Shusaku Tsumoto, Shoji Hirano: Statistical Independence and Contingency Matrix. ICDM Workshops 2008: 643-648 |
178 | EE | Tsau Young Lin, Shusaku Tsumoto: Qualitative fuzzy sets and granularity. IEEE ICCI 2008: 435-440 |
177 | EE | Shusaku Tsumoto, Shoji Hirano: Fuzziness from attribute generalization in information table. IEEE ICCI 2008: 455-461 |
176 | EE | Shusaku Tsumoto, Shoji Hirano: Statistical independence in three-variables contingency cube. IEEE ICCI 2008: 468-474 |
175 | EE | Hidenao Abe, Shusaku Tsumoto: Analyzing Behavior of Objective Rule Evaluation Indices Based on Pearson Product-Moment Correlation Coefficient. ISMIS 2008: 84-89 |
174 | EE | Hidenao Abe, Shusaku Tsumoto: Analyzing Behavior of Objective Rule Evaluation Indices Based on a Correlation Coefficient. KES (2) 2008: 758-765 |
173 | EE | Shoji Hirano, Shusaku Tsumoto: Detection of Risk Factors as Temporal Data Mining. PAKDD Workshops 2008: 143-156 |
172 | EE | Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Finding Functional Groups of Objective Rule Evaluation Indices Using PCA. PAKM 2008: 197-206 |
171 | EE | Shusaku Tsumoto, Shoji Hirano: Statistical Independence of Multi-variables from the Viewpoint of Linear Algebra. RSCTC 2008: 103-112 |
170 | EE | Hidenao Abe, Shusaku Tsumoto: Implementing a Rule Generation Method Based on Secondary Differences of Two Criteria. RSCTC 2008: 293-298 |
169 | EE | Shoji Hirano, Shusaku Tsumoto: Hierarchical Clustering of Non-Euclidean Relational Data Using Indiscernibility-Level. RSKT 2008: 332-339 |
168 | EE | Hidenao Abe, Shusaku Tsumoto: Analyzing Correlation Coefficients of Objective Rule Evaluation Indices on Classification Rules. RSKT 2008: 467-474 |
167 | EE | 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 |
166 | EE | Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating Learning Algorithms to Support Human Rule Evaluation with Predicting Interestingness Based on Objective Rule Evaluation Indices. Communications and Discoveries from Multidisciplinary Data 2008: 269-282 |
165 | EE | Shusaku Tsumoto, Kimiko Matsuoka, Shigeki Yokoyama: Risk Mining for Infection Control. Communications and Discoveries from Multidisciplinary Data 2008: 283-297 |
164 | EE | Shusaku Tsumoto: On Pseudo-Statistical Independence in a Contingency Table. Data Mining: Foundations and Practice 2008: 387-403 |
163 | EE | Shusaku Tsumoto: Role of Sample Size and Determinants in Granularity of Contingency Matrix. Data Mining: Foundations and Practice 2008: 405-421 |
162 | EE | Shusaku Tsumoto, Shoji Hirano: Contingency Matrix Theory I: Rank and Statistical Independence in a Contigency Table. Transactions on Computational Science 2: 161-179 (2008) |
2007 | ||
161 | EE | Kimiko Matsuoka, Shigeki Yokoyama, Kunitomo Watanabe, Shusaku Tsumoto: Mining Rules for Risk Factors on Blood Stream Infection in Hospital Information System. BIBM 2007: 181-187 |
160 | EE | Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Hideto Yokoi, Takahira Yamaguchi: Evaluation of Learning Costs of Rule Evaluation Models Based on Objective Indices to Predict Human Hypothesis Construction Phases. GrC 2007: 458-464 |
159 | EE | Shusaku Tsumoto, Shoji Hirano: Meaning of Pearson Residuals - Linear Algebra View. GrC 2007: 465-470 |
158 | EE | Shusaku Tsumoto: Mining Diagnostic Taxonomy and Diagnostic Rules for Multi-Stage Medical Diagnosis from Hospital Clinical Data. GrC 2007: 611-616 |
157 | EE | 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 |
156 | EE | Kimiko Matsuoka, Shigeki Yokoyama, Kumitomo Watanabe, Shusaku Tsumoto: Analysis of Relationship between Blood Stream Infection and Clinical Background in Patients Lactobacillus Therapy by Data Mining. ICDM Workshops 2007: 175-180 |
155 | EE | Shusaku Tsumoto, Shoji Hirano: Charcteristics of Pearson Residuals in a Contingency Matrix. IEEE ICCI 2007: 195-204 |
154 | EE | Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating Learning Algorithms to Construct Rule Evaluation Models Based on Objective Rule Evaluation Indices. IEEE ICCI 2007: 212-221 |
153 | EE | Takashi Washio, Shusaku Tsumoto: International Workshop on Risk Informatics (RI2007). JSAI 2007: 245-246 |
152 | EE | Kimiko Matsuoka, Shigeki Yokoyama, Kunitomo Watanabe, Shusaku Tsumoto: Data Mining Analysis of Relationship Between Blood Stream Infection and Clinical Background in Patients Undergoing Lactobacillus Therapy. JSAI 2007: 277-288 |
151 | EE | Shoji Hirano, Shusaku Tsumoto: Discovery of Risky Cases in Chronic Diseases: An Approach Using Trajectory Grouping. JSAI 2007: 289-302 |
150 | EE | Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating a Constructive Meta-learning Algorithm for a Rule Evaluation Support Method Based on Objective Indices. KES (2) 2007: 934-941 |
149 | EE | Shusaku Tsumoto, Shoji Hirano: Visualization of Similarities and Dissimilarities Between Rules Using Multidimensional Scaling. KES (2) 2007: 978-986 |
148 | EE | Shoji Hirano, Shusaku Tsumoto: Trajectory Analysis of Laboratory Tests as Medical Complex Data Mining. MCD 2007: 27-41 |
147 | EE | Shusaku Tsumoto: Medical Reasoning and Rough Sets. RSEISP 2007: 90-100 |
146 | EE | Shusaku Tsumoto: Attribute Generalization and Fuzziness in Data Mining Contexts. RSFDGrC 2007: 379-386 |
145 | EE | Shoji Hirano, Shusaku Tsumoto: Dealing with granularity on non-euclidean relational data based on indiscernibility level. SMC 2007: 3772-3777 |
144 | EE | Shusaku Tsumoto, Shoji Hirano: Contingency matrix theory. SMC 2007: 3778-3783 |
143 | EE | Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating learning algorithms for a rule evaluation support method. SMC 2007: 3784-3789 |
142 | EE | Miho Ohsaki, Hidenao Abe, Shusaku Tsumoto, Hideto Yokoi, Takahira Yamaguchi: Evaluation of rule interestingness measures in medical knowledge discovery in databases. Artificial Intelligence in Medicine 41(3): 177-196 (2007) |
141 | EE | Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating Learning Algorithms to Support Human Rule - Evaluation Based on Objective Rule Evaluation Indices. Data Science Journal 6: 285-296 (2007) |
140 | EE | Shusaku Tsumoto, Shoji Hirano: Visualization of Differences between Rules' Syntactic and Semantic Similarities using Multidimensional Scaling. Fundam. Inform. 78(4): 561-573 (2007) |
139 | EE | 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) |
2006 | ||
138 | Yukio Ohsawa, Shusaku Tsumoto: Chance Discoveries in Real World Decision Making: Data-based Interaction of Human Intelligence and Artificial Intelligence Springer 2006 | |
137 | Achim G. Hoffmann, Byeong Ho Kang, Debbie Richards, Shusaku Tsumoto: Advances in Knowledge Acquisition and Management, Pacific Rim Knowledge Acquisition Workshop, PKAW 2006, Guilin, China, August 7-8, 2006, Revised Selected Papers Springer 2006 | |
136 | EE | Shusaku Tsumoto: Data Structure and Algorithm in Data Mining: Granular Computing View. COMPSAC (1) 2006: 26-27 |
135 | EE | Shoji Hirano, Shusaku Tsumoto: Cluster Analysis of Time-Series Medical Data Based on the Trajectory Representation and Multiscale Comparison Techniques. ICDM 2006: 896-901 |
134 | EE | Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating Learning Algorithms Composed by a Constructive Meta-Learning Scheme for a Rule Evaluation Support Method. ICDM Workshops 2006: 305-310 |
133 | EE | Shusaku Tsumoto, Shoji Hirano: Residual Matrix and Statistical Independence in a Contingency Table. ICDM Workshops 2006: 433-437 |
132 | EE | Shusaku Tsumoto, Kimiko Matsuoka, Shigeki Yokoyama: Risk Mining in Hospital Information Systems. ICDM Workshops 2006: 699-704 |
131 | EE | Miho Ohsaki, Hidenao Abe, Shusaku Tsumoto, Hideto Yokoi, Takahira Yamaguchi: Proposal of Medical KDD Support User Interface Utilizing Rule Interestingness Measures. ICDM Workshops 2006: 759-764 |
130 | EE | Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating Learning Algorithms for a Rule Evaluation Support Method Based on Objective Rule Evaluation Indices. ISMIS 2006: 379-388 |
129 | EE | Shoji Hirano, Shusaku Tsumoto: Characteristics of Indiscernibility Degree in Rough Clustering Examined Using Perfect Initial Equivalence Relations. ISMIS 2006: 454-462 |
128 | EE | Shusaku Tsumoto, Takashi Washio: Risk Mining - Overview. JSAI 2006: 303-304 |
127 | EE | Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating Model Construction Methods with Objective Rule Evaluation Indices to Support Human Experts. MDAI 2006: 93-104 |
126 | EE | Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating a Rule Evaluation Support Method Based on Objective Rule Evaluation Indices. PAKDD 2006: 509-519 |
125 | EE | Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Hideto Yokoi, Takahira Yamaguchi: Evaluating Learning Algorithms with Meta-learning Schemes for a Rule Evaluation Support Method Based on Objective Indices. PKAW 2006: 75-88 |
124 | EE | Shusaku Tsumoto: Pawlak Rough Set Model, Medical Reasoning and Rule Mining. RSCTC 2006: 53-70 |
123 | EE | Shusaku Tsumoto, Shoji Hirano: Distribution of Determinants of Contingency Matrix. RSCTC 2006: 567-576 |
122 | EE | Shusaku Tsumoto, Shoji Hirano: Interpretation of Contingency Matrix Using Marginal Distributions. RSCTC 2006: 577-586 |
121 | EE | Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Evaluating Learning Models for a Rule Evaluation Support Method Based on Objective Indices. RSCTC 2006: 687-695 |
120 | EE | Shusaku Tsumoto, Kimiko Matsuoka, Shigeki Yokoyama: Risk Mining: Mining Nurses' Incident Factors and Application of Mining Results to Prevention of Incidents. RSCTC 2006: 706-715 |
119 | EE | Shoji Hirano, Shusaku Tsumoto: A Framework for Unsupervised Selection of Indiscernibility Threshold in Rough Clustering. RSCTC 2006: 872-881 |
118 | EE | Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: Developing a Rule Evaluation Support Method Based on Objective Indices. RSKT 2006: 456-461 |
117 | EE | Shusaku Tsumoto, Yuko Tsumoto, Kimiko Matsuoka, Shigeki Yokoyama: Risk Mining in Medicine: Application of Data Mining to Medical Risk Management. WImBI 2006: 471-493 |
116 | EE | Yuko Tsumoto, Shusaku Tsumoto: Mining Hospital Management Data using R. Chance Discoveries in Real World Decision Making 2006: 393-404 |
115 | EE | Shusaku Tsumoto: Statistical Independence as Linear Dependence in a Contingency Table. Foundations and Novel Approaches in Data Mining 2006: 61-73 |
2005 | ||
114 | Shusaku Tsumoto, Takahira Yamaguchi, Masayuki Numao, Hiroshi Motoda: Active Mining, Second International Workshop, AM 2003, Maebashi, Japan, October 28, 2003, Revised Selected Papers Springer 2005 | |
113 | Mohand-Said Hacid, Neil V. Murray, Zbigniew W. Ras, Shusaku Tsumoto: Foundations of Intelligent Systems, 15th International Symposium, ISMIS 2005, Saratoga Springs, NY, USA, May 25-28, 2005, Proceedings Springer 2005 | |
112 | Tsau Young Lin, Setsuo Ohsuga, Churn-Jung Liau, Xiaohua Hu, Shusaku Tsumoto: Foundations of Data Mining and knowledge Discovery Springer 2005 | |
111 | EE | Shoji Hirano, Shusaku Tsumoto: An indiscernibility-based clustering method. GrC 2005: 468-473 |
110 | EE | Shusaku Tsumoto, Shoji Hirano: Degree of Dependence as Granularity in a Contingency Table. GrC 2005: 63-69 |
109 | EE | Shusaku Tsumoto, Shoji Hirano: Linear independence in a contingency table. GrC 2005: 646-651 |
108 | EE | Hidenao Abe, Miho Ohsaki, Shusaku Tsumoto, Takahira Yamaguchi: Evaluating a Rule Evaluation Support Method with Learning Models Based on Objective Rule Evaluation Indices - A Case Study with a Meningitis Data Mining Result. HIS 2005: 169-174 |
107 | EE | Shoji Hirano, Shusaku Tsumoto: Grouping of Soccer Game Records by Multiscale Comparison Technique and Rough Clustering. HIS 2005: 399-404 |
106 | EE | Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi: A Rule Evaluation Support Method with Learning Models Based on Objective Rule Evaluation Indexes. ICDM 2005: 549-552 |
105 | EE | Shusaku Tsumoto, Shoji Hirano: Visualization of Similarities and Dissimilarities in Rules Using Multidimensional Scaling. ISMIS 2005: 38-46 |
104 | EE | Shusaku Tsumoto: Statistical Independence from the Viewpoint of Linear Algebra. ISMIS 2005: 56-64 |
103 | EE | Shoji Hirano, Shusaku Tsumoto: Clustering Time-Series Medical Databases Based on the Improved Multiscale Matching. ISMIS 2005: 612-621 |
102 | EE | Shoji Hirano, Shusaku Tsumoto: On Constructing Clusters from Non-Euclidean Dissimilarity Matrix by Using Rough Clustering. JSAI Workshops 2005: 5-16 |
101 | EE | Shusaku Tsumoto, Shoji Hirano: On Degree of Dependence Based on Contingency Matrix. RSFDGrC (1) 2005: 471-480 |
100 | EE | Shoji Hirano, Shusaku Tsumoto: A Clustering Method for Spatio-temporal Data and Its Application to Soccer Game Records. RSFDGrC (1) 2005: 612-621 |
99 | EE | Shoji Hirano, Shusaku Tsumoto: A Parallel, Structural Comparison Scheme of Time-Series Implemented on a PC Cluster. SAINT Workshops 2005: 344-347 |
98 | EE | Shusaku Tsumoto, Shoji Hirano, Hidenao Abe, Hideaki Nakakuni, Eisuke Hanada: Clinical Decision Support Based on Mobile Telecommunication Systems. Web Intelligence 2005: 700-703 |
97 | EE | Shusaku Tsumoto: On Statistical Independence in a Contingency Table. Foundations of Data Mining and knowledge Discovery 2005: 131-141 |
96 | EE | Shoji Hirano, Shusaku Tsumoto: Rough representation of a region of interest in medical images. Int. J. Approx. Reasoning 40(1-2): 23-34 (2005) |
95 | EE | Shusaku Tsumoto, Shoji Hirano: Automated discovery of chronological patterns in long time-series medical datasets. Int. J. Intell. Syst. 20(7): 737-757 (2005) |
2004 | ||
94 | Shusaku Tsumoto, Roman Slowinski, Henryk Jan Komorowski, Jerzy W. Grzymala-Busse: Rough Sets and Current Trends in Computing, 4th International Conference, RSCTC 2004, Uppsala, Sweden, June 1-5, 2004, Proceedings Springer 2004 | |
93 | EE | Shusaku Tsumoto: Mining Diagnostic Taxonomy Using Interval-Based Similarity from Clinical Databases. MDAI 2004: 115-126 |
92 | EE | Shusaku Tsumoto, Shoji Hirano: A Comparative Study of Clustering Methods for Long Time-Series Medical Databases. MDAI 2004: 260-272 |
91 | EE | Shoji Hirano, Shusaku Tsumoto: Finding Interesting Pass Patterns from Soccer Game Records. PKDD 2004: 209-218 |
90 | EE | Shoji Hirano, Shusaku Tsumoto: On the Degree of Independence of a Contingency Matrix. Rough Sets and Current Trends in Computing 2004: 219-228 |
89 | EE | Shoji Hirano, Shusaku Tsumoto: Detection of Differences between Syntactic and Semantic Similarities. Rough Sets and Current Trends in Computing 2004: 529-538 |
88 | EE | Shusaku Tsumoto: Extraction of Structure of Medical Diagnosis from Clinical Data. Fundam. Inform. 59(2-3): 271-285 (2004) |
87 | EE | Shoji Hirano, Xiaoguang Sun, Shusaku Tsumoto: Comparison of clustering methods for clinical databases. Inf. Sci. 159(2): 155-165 (2004) |
86 | EE | Shusaku Tsumoto: Mining diagnostic rules from clinical databases using rough sets and medical diagnostic model. Inf. Sci. 162(2): 65-80 (2004) |
2003 | ||
85 | Ning Zhong, Zbigniew W. Ras, Shusaku Tsumoto, Einoshin Suzuki: Foundations of Intelligent Systems, 14th International Symposium, ISMIS 2003, Maebashi City, Japan, October 28-31, 2003, Proceedings Springer 2003 | |
84 | EE | Shusaku Tsumoto, Takahira Yamaguchi, Masayuki Numao, Hiroshi Motoda: Active Mining Project: Overview. Active Mining 2003: 1-10 |
83 | EE | Shoji Hirano, Shusaku Tsumoto: Empirical Comparison of Clustering Methods for Long Time-Series Databases. Active Mining 2003: 268-286 |
82 | EE | Shusaku Tsumoto, Shoji Hirano, Eisuke Hanada: Internet-based Decision Support: Towards E-Hospital. COMPSAC 2003: 595-600 |
81 | EE | Shusaku Tsumoto, Shoji Hirano: Visualization of Rule's Similarity using Multidimensional Scaling. ICDM 2003: 339-346 |
80 | EE | Shusaku Tsumoto, Shoji Hirano: Pattern Discovery based on Rule Induction and Taxonomy Generation. ICDM 2003: 661-664 |
79 | EE | Shusaku Tsumoto: Mining Multi-level Diagnostic Process Rules from Clinical Databases Using Rough Sets and Medical Diagnostic Model. IFSA 2003: 362-369 |
78 | EE | Shoji Hirano, Shusaku Tsumoto: Indiscernibility-Based Clustering: Rough Clustering. IFSA 2003: 378-386 |
77 | EE | Shusaku Tsumoto: Mining Diagnostic Rules with Taxonomy from Medical Databases. ISMIS 2003: 40-48 |
76 | EE | Shoji Hirano, Shusaku Tsumoto: Empirical Evaluation of Dissimilarity Measures for Time-Series Multiscale Matching. ISMIS 2003: 454-462 |
75 | EE | Shoji Hirano, Shusaku Tsumoto: Dealing with Relative Similarity in Clustering: An Indiscernibility Based Approach. PAKDD 2003: 513-518 |
74 | EE | Shoji Hirano, Shusaku Tsumoto: An Indiscernibility-Based Clustering Method with Iterative Refinement of Equivalence Relations. PKDD 2003: 192-203 |
73 | EE | Shusaku Tsumoto: Mining Rules of Multi-level Diagnostic Procedure from Databases. PKDD 2003: 459-470 |
72 | EE | Shusaku Tsumoto: Characteristics of Accuracy and Coverage in Rule Induction. RSFDGrC 2003: 237-244 |
71 | EE | Shusaku Tsumoto: Linear Independence in Contingency Table. RSFDGrC 2003: 316-319 |
70 | EE | Shusaku Tsumoto: Extracting Structure of Medical Diagnosis: Rough Set Approach. RSFDGrC 2003: 78-88 |
69 | EE | Shusaku Tsumoto: Web based medical decision support system: application of internet to telemedicine. SAINT Workshops 2003: 288-293 |
68 | EE | Shusaku Tsumoto: Web Based Medical Decision Support System for Neurological Diseases. Web Intelligence 2003: 629-632 |
67 | EE | Shusaku Tsumoto: Rough Set Based Automatic Classification of Musical Instrument Sounds. Electr. Notes Theor. Comput. Sci. 82(4): (2003) |
66 | EE | Shusaku Tsumoto: Statistical Independence as Linear Independence. Electr. Notes Theor. Comput. Sci. 82(4): (2003) |
65 | EE | Shusaku Tsumoto: Automated extraction of hierarchical decision rules from clinical databases using rough set model. Expert Syst. Appl. 24(2): 189-197 (2003) |
64 | EE | Shoji Hirano, Shusaku Tsumoto: An Indiscernibility-Based Clustering Method with Iterative Refinement of Equivalence Relations -Rough Clustering-. JACIII 7(2): 169-177 (2003) |
63 | EE | Shusaku Tsumoto: Chance Discovery in Medicine - Detection of Rare Risky Events in Chronic Diseases. New Generation Comput. 21(2): (2003) |
2002 | ||
62 | EE | Shusaku Tsumoto, Tsau Young Lin, James F. Peters: Foundations of Data Mining via Granular and Rough Computing. COMPSAC 2002: 1123-1124 |
61 | EE | Shoji Hirano, Xiaoguang Sun, Shusaku Tsumoto: On Similarity Measures for Cluster Analysis in Clinical Laboratory Examination Databases. COMPSAC 2002: 1170-1175 |
60 | EE | Shusaku Tsumoto: Rule and Matroid Theory. COMPSAC 2002: 1176-1181 |
59 | EE | Shoji Hirano, Shusaku Tsumoto: Mining Similar Temporal Patterns in Long Time-Series Data and Its Application to Medicine. ICDM 2002: 219-226 |
58 | EE | Shusaku Tsumoto: Automated Discovery of Decision Rule Chains Using Rough Sets and Medical Diagnostic Model. ISMIS 2002: 321-332 |
57 | Shusaku Tsumoto, Shoji Hirano, Akira Yasuda, Kouhei Tsumoto: Analysis of Amino Acid Sequences by Statistical Technique. JCIS 2002: 1169-1173 | |
56 | EE | Shoji Hirano, Shusaku Tsumoto: Multiscale Comparison of Temporal Patternsin Time-Series Medical Databases. PKDD 2002: 188-199 |
55 | EE | Shusaku Tsumoto: Mining Hierarchical Decision Rules from Clinical Databases Using Rough Sets aaand Medical Diagnostic Model. PKDD 2002: 423-434 |
54 | EE | Shusaku Tsumoto: Discovery of Positive and Negative Knowledge in Medical Databases Using Rough Sets. Progress in Discovery Science 2002: 543-552 |
53 | EE | Shusaku Tsumoto: Accuracy and Coverage in Rough Set Rule Induction. Rough Sets and Current Trends in Computing 2002: 373-380 |
52 | EE | Shusaku Tsumoto: Statistical Test for Rough Set Approximation Based on Fisher's Exact Test. Rough Sets and Current Trends in Computing 2002: 381-388 |
51 | EE | 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 |
50 | EE | Shusaku Tsumoto, Shoji Hirano, Akira Yasuda, Kouhei Tsumoto: Analysis of amino-acid sequences by statistical technique. Inf. Sci. 145(3-4): 205-214 (2002) |
2001 | ||
49 | Takao Terano, Toyoaki Nishida, Akira Namatame, Shusaku Tsumoto, Yukio Ohsawa, Takashi Washio: New Frontiers in Artificial Intelligence, Joint JSAI 2001 Workshop Post-Proceedings Springer 2001 | |
48 | EE | Shoji Hirano, Shusaku Tsumoto: A Knowledge-Oriented Clustering Technique Based on Rough Sets. COMPSAC 2001: 632-637 |
47 | 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 | |
46 | Shusaku Tsumoto: Medical Diagnostic Rules As Upper Approximation of Rough Sets. FUZZ-IEEE 2001: 1551-1554 | |
45 | EE | Shoji Hirano, Shusaku Tsumoto: Indiscernibility Degree of Objects for Evaluating Simplicity of Knowledge in the Clustering Procedure. ICDM 2001: 211-217 |
44 | EE | Shusaku Tsumoto, Shoji Hirano, Masahiro Inuiguchi: Workshop on Rough Set Theory and Granular Computing - Summary. JSAI Workshops 2001: 239 |
43 | EE | 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 |
42 | EE | 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 |
41 | EE | Shusaku Tsumoto: Discovery of Temporal Knowledge in Medical Time-Series Databases Using Moving Average, Multiscale Matching, and Rule Induction. PKDD 2001: 448-459 |
40 | EE | Shusaku Tsumoto: Mining Positive and Negative Knowledge in Clinical Databases Based on Rough Set Model. PKDD 2001: 460-471 |
2000 | ||
39 | EE | Shusaku Tsumoto: Problems with Mining Medical Data. COMPSAC 2000: 467-468 |
38 | EE | Shusaku Tsumoto: Discovery of Clinical Knowledge in Hospital Information Systems: Two Case Studies. ISMIS 2000: 573-581 |
37 | Einoshin Suzuki, Shusaku Tsumoto: Evaluating Hypothesis-Driven Exception-Rule Discovery with Medical Data Sets. PAKDD 2000: 208-211 | |
36 | Andrzej Skowron, Jaroslaw Stepaniuk, Shusaku Tsumoto: Information Granules for Spatial Reasoning. PAKDD 2000: 380-383 | |
35 | EE | Shusaku Tsumoto: Clinical Knowledge Discovery in Hospital Information Systems: Two Case Studies. PKDD 2000: 652-656 |
34 | EE | Shusaku Tsumoto: An Approach to Statistical Extention of Rough Set Rule Induction. Rough Sets and Current Trends in Computing 2000: 362-369 |
33 | EE | Shusaku Tsumoto: Diagnostic Reasoning from the Viewpoint of Rough Sets. Rough Sets and Current Trends in Computing 2000: 495-502 |
32 | Shusaku Tsumoto: Knowledge discovery in clinical databases and evaluation of discovered knowledge in outpatient clinic. Inf. Sci. 124(1-4): 125-137 (2000) | |
1999 | ||
31 | Shusaku Tsumoto: Knowledge Discovery in Clinical Databases: An Experiment with Rule Induction and Statistics. ISMIS 1999: 349-357 | |
30 | EE | Shusaku Tsumoto: Automated Discovery of Plausible Rules Based on Rough Sets and Rough Inclusion. PAKDD 1999: 210-219 |
29 | EE | Shusaku Tsumoto: Rule Discovery in Databases with Missing Values Based on Rough Set Model. PAKDD 1999: 274-278 |
28 | Shusaku Tsumoto: Knowledge Discovery in Medical Multi-databases: A Rough Set Approach. PKDD 1999: 147-155 | |
27 | Shusaku Tsumoto: Rule Discovery in Large Time-Series Medical Databases. PKDD 1999: 23-31 | |
26 | Shinsuke Sugaya, Einoshin Suzuki, Shusaku Tsumoto: Support Vector Machines for Knowledge Discovery. PKDD 1999: 561-567 | |
25 | Shusaku Tsumoto, Tsau Young Lin: Context-Free Fuzzy Sets in Data Mining Context. RSFDGrC 1999: 212-220 | |
24 | Shusaku Tsumoto: Discovery of Rules about Compilations - A Rough Set Approach in Medical Knowledge Discovery. RSFDGrC 1999: 29-37 | |
1998 | ||
23 | Shusaku Tsumoto: Discovery of Approximate Medical Knowledge Based on Rough Set Model. PKDD 1998: 468-476 | |
22 | EE | Shusaku Tsumoto: Modelling Medical Diagnostic Rules Based on Rough Sets. Rough Sets and Current Trends in Computing 1998: 475-482 |
21 | Shusaku Tsumoto: Automated Extraction of Medical Expert System Rules from Clinical Databases on Rough Set Theory. Inf. Sci. 112(1-4): 67-84 (1998) | |
20 | EE | Shusaku Tsumoto: Extraction of Experts' Decision Rules from Clinical Databases Using Rough Set Model. Intell. Data Anal. 2(1-4): 215-227 (1998) |
1997 | ||
19 | Shusaku Tsumoto: Induction of Positive and Negative Deterministic Rules based on Rough Set Model. ISMIS 1997: 298-307 | |
18 | Shusaku Tsumoto: Extraction of Experts' Decision Process from Clinical Databases Using Rough Set Model. PKDD 1997: 58-67 | |
1996 | ||
17 | Shusaku Tsumoto, Hiroshi Tanaka: Induction of Expert System Rules from Databases Based on Rough Set Theory and Resampling Methods. ISMIS 1996: 128-138 | |
16 | Shusaku Tsumoto, Wojciech Ziarko: The Application of Rough Sets-Based Data Mining Technique to Differential Diagnosis of Meningoenchepahlitis. ISMIS 1996: 438-447 | |
15 | Shusaku Tsumoto, Hiroshi Tanaka: Automated Discovery of Medical Expert System Rules from Clinical Databases Based on Rough Sets. KDD 1996: 63-69 | |
14 | Shusaku Tsumoto, Hiroshi Tanaka: A Common Algebraic Framework of Empirical Learning Methods Based on Rough Sets and Matroid Theory. Fundam. Inform. 27(2/3): 273-288 (1996) | |
1995 | ||
13 | Shusaku Tsumoto, Hiroshi Tanaka, Hiromi Amano, Kimie Ohyama, Takayuki Kuroda: COBRA: Integration of Knowledge-Bases with Case-Databases in the Domain of Congenital Malformation. AIME 1995: 393-394 | |
12 | Shusaku Tsumoto, Hiroshi Tanaka: Induction of Expert System Rules from Clinical Databases Based on Rough Set Theory and Resampling Methods. AIME 1995: 399-400 | |
11 | Shusaku Tsumoto, Hiroshi Tanaka: Automated Selection of Rule Induction Methods Based on Recursive Iteration of Resampling Methods and Multiple Statistical Testing. KDD 1995: 312-317 | |
10 | Shusaku Tsumoto, Hiroshi Tanaka: Automated Discovery of Functional Components of Proteins from Amino-Acid Sequences Based on Rough Sets and Change of Representation. KDD 1995: 318-324 | |
9 | Shusaku Tsumoto, Hiroshi Tanaka: Algebraic Formulation of Empirical Learning Methods Based on Rough Sets and Matroid Theory. WOCFAI 1995: 393-404 | |
8 | Shusaku Tsumoto, Hiroshi Tanaka: PRIMEROSE: Probabilistic Rule Induction Method based on Rough Sets and Resampling Methods. Computational Intelligence 11: 389-405 (1995) | |
7 | Shusaku Tsumoto, Hiroshi Tanaka, Hiromi Amano, Kimie Ohyama, Takayuki Kuroda: COBRA: Integration of Heterogeneous Knowledge-Bases in Medical Domain. Int. J. Cooperative Inf. Syst. 4(4): 387-404 (1995) | |
1994 | ||
6 | Shusaku Tsumoto, Hiroshi Tanaka: Algebraic Specification of Empirical Inductive Learning Methods based on Rough Sets and Matroid Theory. AISMC 1994: 224-243 | |
5 | Shusaku Tsumoto, Hiroshi Tanaka: Selection of Probabilistic Measure Estimation Method Based on Recursive Iteration of Resampling Methods. KDD Workshop 1994: 121-132 | |
1993 | ||
4 | Shusaku Tsumoto, Hiroshi Tanaka: Induction of Probabilistic Rules Based on Rough Set Theory. ALT 1993: 410-423 | |
3 | Shusaku Tsumoto, Hiroshi Tanaka: PRIMEROSE: Probabilistic Rule Induction Method Based on Rough Set Theory. RSKD 1993: 274-281 | |
2 | Shusaku Tsumoto, Hiroshi Tanaka: AQ, Rough Sets, and Matroid Theory. RSKD 1993: 290-297 | |
1985 | ||
1 | Yasushi Matsumura, Takashi Matsunaga, Yusuke Maeda, Shusaku Tsumoto, Hiroshi Matsumura, Michio Kimura: Consultation System for Diagnosis of Headache and Facial Pain: "RHINOS". LP 1985: 287-298 |