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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Agent-oriented simulation of Emergency Department re-triage based on allocated time to treatment

Agent-oriented simulation of Emergency Department re-triage ...

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IEEE EMBS Conference on Biomedical engineering and Sciences (IECBES)

作者： Muthukkaruppan Annamalai Nur Akidah Khairani Mohammad Hafidz Rahmat Faculty of Computer and Mathematical Sciences Knowledge and Software Engineering Research Group (KaSERG) Universiti Teknologi MARA (UiTM) Selangor Malaysia

Triage is the first point of clinical assessment of severity in Emergency Departments (ED). While patients are allocated maximum waiting time to treatment, it is often overlooked in Malaysian ED. There are situations when patients' clinical conditions have deteriorated while waiting for treatment, which the patients may not have realized. Ideally, as patients reach the allocated waiting time limit, they should be re-triaged in order to re-assess their severity and take action for prompt treatment if necessary. Since, existing Malaysian triage systems do not implement re-triage, we used agent-oriented simulation to study the effects of re-triage on patients with deteriorating clinical conditions. Our preliminary findings show that re-triage can help to reduce the waiting time of patients whose conditions deteriorate rapidly. The simulation also uncovers an ED resource bottleneck, i.e., the number of physicians treating the patients, which is fixed to two based on the advice of practitioners.

关键词： Medical services Computational modeling Conferences Biomedical engineering Queueing analysis Adaptation models Registers

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ROUGH CLUSTERING FOR CANCER DATASETS

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International Journal of Modern Physics: Conference Series 2012年第9期ijmpcs卷 240-258页

作者： TUTUT HERAWAN Database and Knowledge Management Research Group Faculty of Computer System and Software Engineering Universiti Malaysia Pahang Lebuh Raya Tun Razak Gambang 26300 Pahang Malaysia

Cancer is becoming a leading cause of death among people in the whole world. It is confirmed that the early detection and accurate diagnosis of this disease can ensure a long survival of the patients. Expert systems and machine learning techniques are gaining popularity in this field because of the effective classification and high diagnostic capability. This paper presents the application of rough set theory for clustering two cancer datasets. These datasets are taken from UCI ML repository. The method is based on MDA technique proposed by [11]. To select a clustering attribute, the maximal degree of the rough attributes dependencies in categorical-valued information systems is used. Further, we use a divide-and-conquer method to partition/cluster the objects. The results show that MDA technique can be used to cluster to the data. Further, we present clusters visualization using two dimensional plot. The plot results provide user friendly navigation to understand the cluster obtained.

关键词： Clustering rough set MDA technique cancer datasets

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SOFT SET-BASED DECISION MAKING FOR PATIENTS SUSPECTED INFLUENZA-LIKE ILLNESS

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International Journal of Modern Physics: Conference Series 2012年第9期ijmpcs卷 259-270页

In previous work, we presented an applicability of soft set theory for decision making of patients suspected influenza. The proposed technique is based on maximal supported objects by parameters. At this stage of the research, results are presented and discussed from a qualitative point of view against recent soft decision making techniques through an artificial dataset. In this paper, we present an extended application of our soft set-based decision making through a Boolean valued information system from a dataset of patients suspected ILI (Influenza-Like Illness). Using soft set theory and maximal symptoms co-occurences in patients, we explore how soft set-based decision making technique can be used to reduce the number of dispensable symptoms and further make a correct and fast decision. The result of this work can be used for recommendation of decision making based on the clusters decision captured. Finally, this technique may potentially contribute to lowering the complexity of medical decision making without loss of original information.

关键词： Decision making soft set theory ILI dataset

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Tools for environmental data Mining and intelligent Decision Support

Tools for environmental data Mining and intelligent Decision...

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6th Biennial Meeting of the International Environmental Modelling and software Society: Managing Resources of a Limited Planet, iEMSs 2012

作者： Gibert, Karina Sànchez-Marrè, Miquel Sevilla, Beatriz Knowledge Engineering and Machine Learning Group Universitat Politècnica de Catalunya-BarcelonaTech Barcelona Catalonia Spain Department of Statistics and Operation Research Universitat Politècnica de Catalunya-BarcelonaTech Barcelona Catalonia Spain Software Department Universitat Politrcnica de Catalunya-BarcelonaTech Catalonia Spain

ISBN: (纸本)9788890357428

The joint workshop in Data Mining for Environmental Scientists and Intelligent Environmental Decision Support Systems tries to provide a common discussion forum to communicate environmentalists with data miners and intelligent decision support systems developers. As environmentalists are the consumers of both products, Data Mining (DM) and Intelligent Decision Support Systems (IDSS) are complementary disciplines that must properly link to permit the maximum benefits of data analysis at highest levels. Here, a preliminary analysis of the state of the software tools in environmental DM and IDSS is presented.

关键词： Data mining

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Decreasing uncertainty when interpreting profiles through the traffic lights panel

Decreasing uncertainty when interpreting profiles through th...

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14th International Conference on Information Processing and Management of Uncertainty in knowledge-Based Systems, IPMU 2012

作者： Gibert, Karina Conti, Dante Sànchez-Marrè, Miquel Dep. of Statistics and Operation Research Universitat Politècnica de Catalunya Barcelona Spain Knowledge Engineering and Machine Learning Group Universitat Politècnica de Catalunya Barcelona Tech. Spain Dep. of Operations Research Universidad de Los Andes Mérida Venezuela Dep. Software Universitat Politècnica de Catalunya Spain

ISBN: (纸本)9783642317149

This paper describes Traffic Lights Panel (TLP) as a useful interpretation-oriented tool for clustering results, suitable for helping the domain experts to induce a conceptualization of the resulting profiles. Till now, the TLP is manually derived from the clustering results, but it has been well accepted by the domain experts of several real applications as a very helpful contribution to understand the classes' meaning and improve reliable decision-making. Here, a proposal to automatically construction of TLP is presented trying to mimic the real process that the analyst performs. Two criteria based on different central trend statistics of the variables inside a class are introduced, tested with a real case study in Neurorehabilitation field and compared. Finally, uncertainty concerning TLP is analyzed;the annotated TLP (aTLP) is proposed to visualize uncertainty associated to the decisions derived from TLP, thus enhancing robustness of TLP as a supporting tool in decision-making. © 2012 Springer-Verlag.

关键词： Decision making

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Malay anaphor and antecedent candidate identification: A proposed solution

Malay anaphor and antecedent candidate identification: A pro...

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4th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2012

作者： Mohd Noor, Noorhuzaimi Karimah Noah, Shahrul Azman Ab Aziz, Mohd Juzaiddin Hamzah, Mohd Pouzi Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Lebuhraya Tun Razak Pahang Kuantan 26300 Malaysia Knowledge Technology Research Group Faculty of Technology and Information Science Universiti Kebangsaan Malaysia Selangor Bangi 43600 Malaysia Department of Computer Science Faculty of Science Technology Universiti Malaysia Terengganu Terengganu Kuala Terengganu 21030 Malaysia

ISBN: (纸本)9783642284922

This paper discusses on Malay language anaphor and antecedent candidate determination using the knowledge-poor techniques. The process to determine the candidate for anaphor and antecedent is important because the usage of pronouns in a text is not always considered as an anaphor. Sometimes pronoun referred to something outside the context or does not refer to any situation in the text. Such a situation is also exhibited in the use of pronouns in Malay language. Therefore, certain rules must be issued to identify the antecedent and anaphor candidate. Pronoun usage in Malay language does indicate the gender of the person, but to distinguish the status of the person such as imperial family, honorable people and common people. Thus, generic rules that have been used by other languages cannot simply be adapted for Malay language. The proposed solution concerns with the distance of each candidate and location of the Subject-Verb-Object (SVO) used to determine the anaphor candidate. As such, syntactic information, semantic information and distance of anaphor-antecedent are seen important to determine the antecedent candidate. © 2012 Springer-Verlag.

关键词： Semantics

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DETECTING CRITICAL LEAST ASSOCIATION RULES IN MEDICAL DATABASES

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International Journal of Modern Physics: Conference Series 2012年第9期ijmpcs卷 464-479页

作者： ZAILANI ABDULLAH TUTUT HERAWAN MUSTAFA MAT DERIS Department of Computer Science Universiti Malaysia Terengganu Mengabang Telipot Kuala Terengganu 21030 Terengganu Malaysia Database and Knowledge Management Research Group Faculty of Computer System and Software Engineering Universiti Malaysia Pahang Lebuhraya Tun Razak Gambang 26300 Kuantan Pahang Malaysia Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Parit Raja 86400 Batu Pahat Johor Malaysia

Least association rules are corresponded to the rarity or irregularity relationship among itemset in database. Mining these rules is very difficult and rarely focused since it always involves with infrequent and exceptional cases. In certain medical data, detecting these rules is very critical and most valuable. However, mathematical formulation and evaluation of the new proposed measurement are not really impressive. Therefore, in this paper we applied our novel measurement called Critical Relative Support (CRS) to mine the critical least association rules from medical dataset. We also employed our scalable algorithm called Significant Least Pattern Growth algorithm (SLP-Growth) to mine the respective association rules. Experiment with two benchmarked medical datasets, Breast Cancer and Cardiac Single Proton Emission Computed Tomography (SPECT) Images proves that CRS can be used to detect to the pertinent rules and thus verify its scalability.

关键词： Critical least association rules medial data

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Proposing an ISO/IEC 15504-2 compliant method for process capability/maturity models customization

Proposing an ISO/IEC 15504-2 compliant method for process ca...

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Lecture Notes in Computer Science

作者： Hauck, Jean Carlo Rossa Von Wangenheim, Christiane Gresse Mc Caffery, Fergal Buglione, Luigi Graduate Program in Knowledge Engineering and Management Federal University of Santa Catarina Brazil Regulated Software Research Group Lero - Dundalk Institute of Technology Ireland Federal University of Santa Catarina Brazil ETS/Engineering.IT Rome Italy

ISBN: (纸本)9783642218422

The customization of software process capability/maturity models (SPCMMs) to specific domains/sectors or development methodologies represents one of the most discussed and applied trends in ICT organizations. Nonetheless, little research appears to have been performed on how theoretically sound and widely accepted SPCMMs should be developed to high quality. The aim of this paper is therefore to elicit the state-of-the-art regarding the processes adopted to develop such models and to propose a systematic approach to support the customization of SPCMMs. Such an approach is developed based on ISO/IEEE standard development processes integrating knowledge engineering techniques and experiences about how such models are currently developed in practice. Initial feedback from an expert panel indicates the usefulness and adequacy of the proposed method. © 2011 Springer-Verlag.

关键词： knowledge engineering

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Visual exploration of time-oriented patient data for chronic diseases: Design study and evaluation

Visual exploration of time-oriented patient data for chronic...

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7th Conference of the Workgroup Human-Computer Interaction and Usability engineering of the Austrian Computer Society, USAB 2011

作者： Rind, Alexander Aigner, Wolfgang Miksch, Silvia Wiltner, Sylvia Pohl, Margit Turic, Thomas Drexler, Felix Institute of Software Technology and Interactive Systems Vienna University of Technology Austria Research Group Human Computer Interaction Vienna University of Technology Austria Department of Information and Knowledge Engineering Danube University Krems Austria Landesklinikum Krems Austria

ISBN: (纸本)9783642253638

Medical care, particularly for chronic diseases, accumulates a huge amount of patient data over extensive time periods that needs to be accessed and analyzed accordingly. Information Visualization methods hold great promises in turning data deluge into improved quality of medical care. Yet, patient data management systems mostly provide documents, form-based displays, or static visualizations. We present a design study of an interactive visualization system, called VisuExplore, to support long-term care and medical analysis of patients with chronic diseases. VisuExplore offers interaction techniques for effective exploration of time-oriented data and employs simple, but intuitive visualization techniques. It was developed in close cooperation with physicians. We conducted two user studies with nine physicians and 16 students, which indicate that our design is useful and appropriate for particular tasks. © 2011 Springer-Verlag Berlin.

关键词： Medical information systems

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