By Daniel J. Olsher (auth.), Huaguang Zhang, Amir Hussain, Derong Liu, Zhanshan Wang (eds.)
This publication constitutes the refereed court cases of the fifth overseas convention on mind encouraged Cognitive structures, BICS 2012, held in Shenyang, Liaoning, China in July 2012. The forty six top quality papers awarded have been conscientiously reviewed and chosen from 116 submissions. The papers are prepared in topical sections on biologically encouraged structures, cognitive neuroscience, versions of realization, and neural computation.
Read Online or Download Advances in Brain Inspired Cognitive Systems: 5th International Conference, BICS 2012, Shenyang, China, July 11-14, 2012. Proceedings PDF
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This booklet constitutes the refereed complaints of the fifth overseas convention on mind encouraged Cognitive platforms, BICS 2012, held in Shenyang, Liaoning, China in July 2012. The forty six fine quality papers offered have been conscientiously reviewed and chosen from 116 submissions. The papers are equipped in topical sections on biologically encouraged platforms, cognitive neuroscience, versions of recognition, and neural computation.
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Extra resources for Advances in Brain Inspired Cognitive Systems: 5th International Conference, BICS 2012, Shenyang, China, July 11-14, 2012. Proceedings
An Ontology-Based Bayesian Network Approach for Representing Uncertainty in Clinical Practice Guidelines. , Pool, M. ) URSW 2005 - 2007. LNCS (LNAI), vol. 5327, pp. 161–173. : Experience of Using OWL Ontologies for Automated Inference of Routine Pre-Operative Screening Tests. : Ontology-Driven Adaptive Medical Information Collection System. , Ślęzak, D. ) ISMIS 2008. LNCS (LNAI), vol. 4994, pp. 574–584. : Sentic PROMs: Application of sentic computing to the development of a novel unified framework for measuring health-care quality.
Conclusions We have presented an ontology driven and Bayesian Network based cardiovascular decision support framework. We have discussed the development of the key components which are Adaptive Information collection system using chest pain risk assessment questionnaire ontology and Patient Semantic Profile for the generation of Electronic Healthcare Records. We also presented a Bayesian Network for uncertainty modelling using Electronic Healthcare Records which have been developed as part of the cardiovascular decision support framework to facilitate accurate and effective clinical decision making.
Coleman segment of the task (planning – start of the task until first cut, executing – after first cut until last cut, ending – after last cut until stopping the task). Before analyzing the data, outliers were removed from each of the dependent measures using a criterion of 3 standard deviations. 2 Experiment 2 Results and Discussion Results. Data was were analyzed by mixed ANOVAs, with working memory capacity (HWM vs. LWM) as the between-subject factor and task demand (low vs. high) as the within-subject factor, and performed separately for accuracy, risk, and fixation duration by segment.