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MicroCBR: A case-based reasoning architecture for the classification of microarray data.

, , , and . Appl. Soft Comput., 11 (8): 4496-4507 (2011)

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A novel hybrid intelligent system for multi-objective machine parameter optimization., , , , and . Pattern Anal. Appl., 18 (1): 31-44 (2015)A Hybrid System for Dental Milling Parameters Optimisation., , , , , , , and . HAIS (2), volume 6679 of Lecture Notes in Computer Science, page 437-446. Springer, (2011)Application of Soft Computing Technologies toward Assessment and Skills Development., , , , , , , and . CISIS/ICEUTE/SOCO Special Sessions, volume 189 of Advances in Intelligent Systems and Computing, page 299-310. Springer, (2012)Evaluation of Novel Soft Computing Methods for the Prediction of the Dental Milling Time-Error Parameter., , , , , , , , , and 1 other author(s). SOCO, volume 188 of Advances in Intelligent Systems and Computing, page 163-172. Springer, (2012)Prediction and failure analysis of composite resin restorations in the posterior sector applied in teaching dental students., , , , and . J. Ambient Intell. Humaniz. Comput., 11 (11): 4537-4544 (2020)Automatic computation of mandibular indices in dental panoramic radiographs for early osteoporosis detection., , , , , and . Artif. Intell. Medicine, (2020)Applying soft computing techniques to optimise a dental milling process., , , , and . Neurocomputing, (2013)Soft Computing Techniques for Skills Assessment of Highly Qualified Personnel., , , , , , and . SOCO-CISIS-ICEUTE, volume 239 of Advances in Intelligent Systems and Computing, page 669-678. Springer, (2013)Optimizing a dental milling process by means of soft computing techniques., , , , , , , , and . ISDA, page 1430-1435. IEEE, (2010)Prediction of Dental Milling Time-Error by Flexible Neural Trees and Fuzzy Rules., , , , , , , , , and 1 other author(s). IDEAL, volume 7435 of Lecture Notes in Computer Science, page 842-849. Springer, (2012)