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OP16.04: User satisfaction with the Clinical data Miner electronic data capture software

Ultrasound in Obstetrics &Gynecology 2014年第S1期44卷 112-112页

作者： A. Installé T. Van den Bosch T. Bourne B. De Moor D. Timmerman Department of Electrical Engineering (ESAT) - STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium iMinds Medical IT KU Leuven Leuven Belgium KU Leuven Department of Obstetrics and Gynecology UZ Leuven Leuven Belgium Department of Obstetrics and Gynecology Imperial College London London United Kingdom KU Leuven Department of Development and Regeneration UZ Leuven Leuven Belgium Department of Electrical Engineering (ESAT) - STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium iMinds Medical IT KU Leuven Leuven Belgium KU Leuven Department of Obstetrics and Gynecology UZ Leuven Leuven Belgium KU Leuven Department of Development and Regeneration UZ Leuven Leuven Belgium

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Novel SNP improves differential survivability and mortality in non-small cell lung cancer patients

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BMC Genomics 2014年第9期15卷 S20-S20页

作者： Mah, Tzia Liang Yap, Xin Ning Adeline Limviphuvadh, Vachiranee Li, Nanpu Sridharan, Srinath Kuralmani, Vellaisemy Feng, Mengling Liem, Natalia Adhikari, Sharmila Yong, Wei Peng Soo, Ross A Maurer-Stroh, Sebastian Eisenhaber, Frank Tong, Joo Chuan Institute for Infocomm Research Data Analytics Department 1 Fusionopolis Way #21-01 Connexis South Tower Singapore 138632 Singapore National University Health System Department of Haematology-Oncology 5 Lower Kent Ridge Road Singapore 119074 Singapore Bioinformatics Institute 30 Biopolis Street #07-01 Matrix Singapore 138671 Singapore Nanyang Technological University (NTU) School of Biological Sciences (SBS) 60 Nanyang Drive 637551 Singapore Nanyang Technological University (NTU) School of Computer Engineering (SCE) 50 Nanyang Drive 637553 Singapore National University of Singapore (NUS) Department of Biological Sciences (DBS) 8 Medical Drive 4 117597 Singapore National University of Singapore Department of Biochemistry Yong Loo Lin School of Medicine Singapore 117597 Singapore Institute of High Performance Computing 1 Fusionopolis Way #16-16 Connexis 138632 Singapore National University of Singapore Cancer Science Institute of Singapore Singapore

Background: Non-small cell lung cancer (NSCLC) is a major cause of cancer-related death worldwide due to poor patient prognosis and clinical outcome. Here, we studied the genetic variations underlying NSCLC pathogenesis based on their association to patient outcome after gemcitabine therapy. Results: Bioinformatics analysis was used to investigate possible effects of POLA2 G583R (POLA2+1747 GG/GA, dbSNP ID: rs487989) in terms of protein function. Using biostatistics, POLA2+1747 GG/GA (rs487989, POLA2 G583R) was identified as strongly associated with mortality rate and survival time among NSCLC patients. It was also shown that POLA2+1747 GG/GA is functionally significant for protein localization via green fluorescent protein (GFP)-tagging and confocal laser scanning microscopy analysis. The single nucleotide polymorphism (SNP) causes DNA polymerase alpha subunit B to localize in the cytoplasm instead of the nucleus. This inhibits DNA replication in cancer cells and confers a protective effect in individuals with this SNP. Conclusions: The results suggest that POLA2+1747 GG/GA may be used as a prognostic biomarker of patient outcome in NSCLC pathogenesis. © 2014 Mah et al.;licensee BioMed Central Ltd.

关键词： Biomarker Genetic variant Mortality Non-small cell lung cancer Survival Outcome

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A prototypical implementation of the intelligent integrated computer-assisted language learning (iiCALL) environment

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11th International Conference on Advances in Web-Based Learning, ICWL 2012

作者： Wahl, Harald Winiwarter, Werner Dept. of Information Engineering and Security University of Applied Sciences Technikum Wien Vienna Austria Research Group Data Analytics and Computing University of Vienna Vienna Austria

ISBN: (纸本)9783642336416

Since the late nineties, several Computer-Assisted Language Learning (CALL) platforms have been developed. By using Natural Language Processing (NLP) and Artificial Intelligence (AI) technologies, CALL has become Intelligent CALL (ICALL). Our research additionally deals with language learning integrated in different environments, be it Web browsers or Email clients. Therefore, we develop a Web-based e-learning solution, called Intelligent Integrated Computer-Assisted Language Learning (iiCALL) platform. Requirements engineering for iiCALL has primarily been done on the basis of identifying suitable use cases with respect to different learning types. Moreover, we face varying levels of learners. The paper illustrates relevant use cases and describes the yielding Web-based and distributed system architecture of iiCALL. Furthermore, it draws specific attention to a first prototype integrated into Mozilla Firefox that implements a simple learning scenario for language learners on a beginner's level. Finally, it points out open issues and future work. © 2012 Springer-Verlag.

关键词： Computer aided instruction

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Using an atlas-based approach in the analysis of gene expression maps obtained by voxelation

Using an atlas-based approach in the analysis of gene expres...

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8th International Workshop on Artificial Intelligence Applications and Innovations, AIAI 2012: AIAB, AIeIA, CISE, COPA, IIVC, ISQL, MHDW, and WADTMB

作者： Zacharaki, Evangelia I. Skoura, Angeliki An, Li Smith, Desmond J. Megalooikonomou, Vasileios Department of Computer Engineering and Informatics University of Patras Patras Greece Data Engineering Laboratory Center for Data Analytics and Biomedical Informatics Temple University PA United States Department of Molecular and Medical Pharmacology David Geffen School of Medicine UCLA CA United States

ISBN: (纸本)9783642334115

The integration of gene expression datasets with gene function information provides valuable insights in unraveling the molecular mechanisms of the brain. In this paper, gene expression maps, acquired by the technique of voxelation, are analyzed using an atlas-based framework and the extracted spatial information is employed to organize genes in significant clusters. Moreover, gene function enrichment analysis of clusters enables exploring the relationships among brain regions, gene expressions and gene functions. Our work confirms the hypothesis that genes of similar spatial expression patterns display similar functions indicating that our methodology could assist in the functional identification of unannotated genes. © 2012 IFIP International Federation for Information Processing.

关键词： Brain mapping

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Towards understanding dominant processes in complex dynamical systems: Case of precipitation extremes

Towards understanding dominant processes in complex dynamica...

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6th International Workshop on Knowledge Discovery from Sensor data, SensorKDD'12 - Held in Conjunction with the 18th ACM SIGKDD Conference on Knowledge Discovery and data Mining, KDD 2012

作者： Das, Debasish Ganguly, Auroop Banerjee, Arindam Obradovic, Zoran Department of Civil and Environmental Engineering Northeastern University Boston MA United States Center for Data Analytics and Biomedical Informatics Temple University Philadelphia PA United States Computer Science and Engineering University of Minnesota Minneapolis MN United States

ISBN: (纸本)9781450315548

Complex dynamical systems like precipitation extremes under climate variability or change are typically governed by multiple processes at multiple scales. The processes themselves may be manifested at multiple scales and would need to be captured through key indicator variables, which in turn may be better projected by physical models than the variables of interest. We posit that hybrid approaches based on physically-motivated approaches and data-driven methods, which in turn are conditioned on both observations and simulations from large-scale physics-based models, may offer novel and quantifiable insights. The data-driven approaches may need to extend and adapt methods developed and tested in statistics, data mining and machine learning to the concept of dominant processes. In this paper, we performed some exploratory data analysis to characterize the effect of dominant processes on precipitation extremes, annually and seasonally, and from global and century scale to regional and decadal scale, and found some interesting insights that pointed towards need of improved understanding. We identified the gaps in understanding the regional drivers where data-driven methods can make useful improvements and eventually lead to a predictive model for precipitation extremes. Although we do not propose any specific method for solving the problem, we realize that any successful data mining solution should include all or a subset of tools like dimensionality reduction, grouped variable selection, non-linear regression and graphical models. The concepts of dominant processes proposed here would likely generalize broadly to climate extremes while the solution frameworks themselves may generalize beyond climate. Copyright 2012 ACM.

关键词： data mining

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Methods for Evaluating Medical Tests and Biomarkers

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Diagnostic and Prognostic Research 2017年第1期1卷 1-34页

作者： Gowri Gopalakrishna Miranda Langendam Patrick Bossuyt Mariska Leeflang Rob Scholten Anna Noel-Storr James Thomas Iain Marshall Byron Wallace Penny Whiting Clare Davenport Gowri GopalaKrishna Isabel de Salis Sue Mallett Robert Wolff Marie Westwood Jos Kleinen Richard Riley Gary Collins Hans Reitsma Karel Moons Antonia Zapf Katharina Kramer Annika Hoyer Oliver Kuss J. Ensor R. D. Riley J. J. Deeks E. C. Martin Gerta Rücker Martin Schumacher Susanne Steinhauser Joie Ensor Kym Snell Brian Willis Jon Deeks Thomas Debray Lavinia Ferrante di Ruffano Sian Taylor-Phillips Chris Hyde Stuart A. Taylor Gauraang Batnagar Lavinia Ferrante Di Ruffano Farah Seedat Aileen Clarke Sarah Byron Frances Nixon Rebecca Albrow Thomas Walker Carla Deakin Zhivko Zhelev Harriet Hunt Yaling Yang Lucy Abel James Buchanan Thomas Fanshawe Bethany Shinkins Laure Wynants Sabine Van Huffel Jan Verbakel Dirk Timmerman Ben Van Calster Aeliko Zwinderman Jason Oke Jack O’Sullivan Rafael Perera Brian Nicholson Hannah L. Bromley Tracy E. Roberts Adele Francis Denniis Petrie G. Bruce Mann Kinga Malottki Holly Smith Lucinda Billingham Alice Sitch Oke Gerke Mie Holm-Vilstrup Eivind Antonsen Segtnan Ulrich Halekoh Poul Flemming Høilund-Carlsen Bernard G. Francq Jac Dinnes Julie Parkes Walter Gregory Jenny Hewison Peter Selby Doug Altman William Rosenberg Julien Asselineau Paul Perez Aïssatou Paye Emilie Bessede Cécile Proust-Lima Christiana Naaktgeboren Joris de Groot Johannes Reitsma Anne Rutjes Emmanuel Ogundimu Jonathan Cook Yannick Le Manach Yvonne Vergouwe Romin Pajouheshnia Rolf Groenwold Karen Moons Linda Peelen Bavo De Cock Daan Nieboer Ewout W. Steyerberg Micael J. Pencina Jennifer Cooper Nick Parsons Chris Stinton Steve Smith Andy Dickens Rachel Jordan Alexandra Enocson David Fitzmaurice Peymane Adab Charles Boachie Gaj Vidmar Karoline Freeman Martin Connock Rachel Court Carl Moons Jessica Harris Zoe Plummer Barnaby Reeves Chris Rogers Andrew Mumford Kurtis Lee Veerle Verheyden Gianni D. Angelini Gavin J. Murphy Jeremy Huddy Melody Ni George Hanna Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands Department of Clinical Epidemiology and Biostatistics Academic Medical Center University of Amsterdam Amsterdam Netherlands Cochrane Netherlands Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht Netherlands Cochrane Dementia and Cognitive Improvement Group University of Oxford Oxford UK EPPI-Centre Department of Social Science University College London London UK Division of Health and Social Care Research King’s College London London UK College of Computer and Information Science Northeastern University Boston USA University Hospitals Bristol NHS Foundation Trust School of Social and Community Medicine Bristol UK Institute of Applied Health Research University of Birmingham Birmingham UK School of Social and Community Medicine University of Bristol Bristol UK Kleijnen Systematic Reviews Ltd York UK Research Institute for Primary Care and Health Sciences Keele University Keele UK Centre for Statistics in Medicine Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences University of Oxford Oxford UK Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht The Netherlands Cochrane Netherlands University Medical Center Utrecht Utrecht The Netherlands Julius Center for Health Sciences and Primary Care University Medical Center Utrecht 3584 CG Utrecht Netherlands Department of Medical Statistics University Medical Center Göttingen Göttingen Germany Institute for Biometry and Epidemiology German Diabetes Center Leibniz Institute for Diabetes Research at Heinrich Heine University Düsseldorf Germany Manchester Pharmacy School University of Manchester Manchester UK Institute for Medical Biometry and Statistics Faculty of Medicine and Medical Center – University of Freiburg Stefan-Meier-Str. 26 79104 Freiburg Germany

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Combining gene expression and function in a spatially localized approach 2012

Combining gene expression and function in a spatially locali...

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2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM2012

作者： Zacharaki, Evangelia I. Skoura, Angeliki Smith, Desmond J. Faro, Scott H. An, Li Megalooikonomou, Vasileios Department of Computer Engineering and Informatics University of Patras Patras Greece Department of Molecular and Medical Pharmacology David Geffen School of Medicine UCLA Los Angeles CA United States Department of Radiology Temple University School of Medicine Philadelphia PA United States Data Engineering Laboratory Center for Data Analytics and Biomedicai Informatics Temple University Philadelphia PA United States

ISBN: (纸本)9781467325585

The integration of gene expression datasets with gene function information provides valuable insights in unraveling the molecular mechanisms of the brain. In this paper, gene expression maps, acquired by the technique of voxelation, are analyzed using an atlas-based framework and the extracted spatial information is employed to organize genes in significant clusters. Gene function enrichment analysis of clusters enabled exploration of the relationships among brain regions, gene expression and gene function. In addition, the analysis revealed new function categories, for example biological process for the gene Pbx3, cellular component and biological process for the gene Ppplrlb. Our work confirms the hypothesis that genes of similar spatial expression patterns display similar functions indicating that our methodology could assist in the function identification of unannotated genes. © 2012 IEEE.

关键词： Brain mapping

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14th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2012

作者： Wahl, Harald Winiwarter, Werner University of Applied Sciences Technikum Wien Dept. of Information Engineering and Security Höchstädtplatz 5 1200 Vienna Austria University of Vienna Research Group Data Analytics and Computing Währinger Straße 29 1090 Vienna Austria

ISBN: (纸本)9781450313063

The Integrated Intelligent Computer-Assisted Language Learning (iiCALL) environment is a Web-based e-learning platform that enables language learning in common working environments like Web browsers or email clients. Based on learning theories, it offers context-related learning scenarios for different learning types and different levels of learners. So far, the prototype implements the server architecture which runs inside an Apache Tomcat using Hibernate and MySQL for persistence purposes and which uses the General Architecture for Text engineering (GATE) framework for Natural Language Processing (NLP) tasks. The prototype also implements a client as a Mozilla Firefox extension by using the XML User Interface Language (XUL) and JavaScript. It exemplarily shows a context-related vocabulary trainer, a learning scenario for language learners on a beginner's level. The paper explains technology of the prototype and points out open issues and future work. © 2012 ACM.

关键词： User interfaces

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The AAAI-13 conference workshops

The AAAI-13 conference workshops

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作者： Agrawal, Vikas Archibald, Christopher Bhatt, Mehul Bui, Hung Cook, Diane J. Cortés, Juan Geib, Christopher Gogate, Vibhav Guesgen, Hans W. Jannach, Dietmar Johanson, Michael Kersting, Kristian Konidaris, George Kotthoff, Lars Michalowski, Martin Natarajan, Sriraam O'Sullivan, Barry Pickett, Marc Podobnik, Vedran Poole, David Shastri, Lokendra Shehu, Amarda Sukthankar, Gita IBM Research India Mississippi State University United States University of Bremen Germany Laboratory for Natural Language Understanding Sunnyvale CA United States Washington State University United States University of Toulouse France Drexel University United States Department of Computer Science University of Texas Dallas United States Massey University New Zealand TU Dortmund Germany University of Alberta in Edmonton Canada Fraunhofer IAIS and the University of Bonn Germany MIT United States INSIGHT Centre for Data Analytics University College Cork Ireland Adventium Labs Minneapolis MN United States Indiana University Bloomington IN United States Naval Research Laboratory Washington DC United States Telecommunication Department of the Faculty of Electrical Engineering and Computing University of Zagreb Croatia Department of Computer Science University of British Columbia Vancouver Canada Infosys India George Mason University United States University of Central Florida United States

The AAAI-13 Workshop Program, a part of the 27th AAAI Conference on Artificial Intelligence, was held Sunday and Monday, July 14-15, 2013, at the Hyatt Regency Bellevue Hotel in Bellevue, Washington, USA. The program included 12 workshops covering a wide range of topics in artificial intelligence, including Activity Context-Aware System Architectures (WS-13-05);Artificial Intelligence and Robotics Methods in Computational Biology (WS-13-06);Combining Constraint Solving with Mining and Learning (WS-13-07);Computer Poker and Imperfect Information (WS-13-08);Expanding the Boundaries of Health Informatics Using Artificial Intelligence (WS-13-09);Intelligent Robotic Systems (WS-13-10);Intelligent Techniques for Web Personalization and Recommendation (WS- 13-11);Learning Rich Representations from Low-Level Sensors (WS-13-12);Plan, Activity, and Intent Recognition (WS-13-13);Space, Time, and Ambient Intelligence (WS-13-14);Trading Agent Design and Analysis (WS-13-15);and Statistical Relational Artificial Intelligence (WS-13-16). Copyright © 2013, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： data mining

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A quantitative evaluation of techniques for detection of abnormal change events in blogs. 12

A quantitative evaluation of techniques for detection of abn...

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12th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL '12

作者： Bogen II, Paul L. Furuta, Richard Shipman, Frank Intelligent Computing Research Team Computational Data Analytics Group Oak Ridge National Laboratory Oak Ridge TN United States Center for the Study of Digital Libraries Dept. of Computer Science and Engineering Texas A and M University College Station TX 77843 United States

ISBN: (纸本)9781450311540

While most digital collections have limited forms of change - primarily creation and deletion of additional resources - there exists a class of digital collections that undergoes additional kinds of change. These collections are made up of resources that are distributed across the Internet and brought together into a collection via hyperlinking. Resources in these collections can be expected to change as time goes on. Part of the difficulty in maintaining these collections is determining if a changed page is still a valid member of the collection. Others have tried to address this problem by measuring change and defining a maximum allowed threshold of change, however, these methods treat all change as a potential problem and treat web content as a static document despite its intrinsically dynamic nature. Instead, we approach the significance of change on the web as a normal part of a web document's life-cycle and determine the difference between what a maintainer expects a page to do and what it actually does. In this work we evaluate the different options for extractors and analyzers in order to determine the best options from a suite of techniques. The evaluation used a human-generated ground-truth set of blog changes. The results of this work showed a statistically significant improvement over a range of traditional threshold techniques when applied to our collection of tagged blog changes. © 2012 ACM.

关键词： Pattern recognition

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