Table Of ContentLecture Notes in Computer Science 7451
CommencedPublicationin1973
FoundingandFormerSeriesEditors:
GerhardGoos,JurisHartmanis,andJanvanLeeuwen
EditorialBoard
DavidHutchison
LancasterUniversity,UK
TakeoKanade
CarnegieMellonUniversity,Pittsburgh,PA,USA
JosefKittler
UniversityofSurrey,Guildford,UK
JonM.Kleinberg
CornellUniversity,Ithaca,NY,USA
AlfredKobsa
UniversityofCalifornia,Irvine,CA,USA
FriedemannMattern
ETHZurich,Switzerland
JohnC.Mitchell
StanfordUniversity,CA,USA
MoniNaor
WeizmannInstituteofScience,Rehovot,Israel
OscarNierstrasz
UniversityofBern,Switzerland
C.PanduRangan
IndianInstituteofTechnology,Madras,India
BernhardSteffen
TUDortmundUniversity,Germany
MadhuSudan
MicrosoftResearch,Cambridge,MA,USA
DemetriTerzopoulos
UniversityofCalifornia,LosAngeles,CA,USA
DougTygar
UniversityofCalifornia,Berkeley,CA,USA
GerhardWeikum
MaxPlanckInstituteforInformatics,Saarbruecken,Germany
Christian Böhm Sami Khuri
Lenka Lhotská M. Elena Renda (Eds.)
Information Technology
in Bio- and
Medical Informatics
Third International Conference, ITBAM 2012
Vienna, Austria, September 4-5, 2012
Proceedings
1 3
VolumeEditors
ChristianBöhm
Ludwig-Maximilians-University,DepartmentofComputerScience
Oettingenstraße67,80538München,Germany
E-mail:[email protected]fi.lmu.de
SamiKhuri
SanJoséStateUniversity,DepartmentofComputerScience
OneWashingtonSquare,SanJosé,CA95192-0249,USA
E-mail:[email protected]
LenkaLhotská
CzechTechnicalUniversity,FacultyofElectricalEngineering
DepartmentofCybernetics
Technicka2,16627Prague6,CzechRepublic
E-mail:[email protected]
M.ElenaRenda
IstitutodiInformaticaeTelematicadelCNR
ViaG.Moruzzi1,56124Pisa,Italy
E-mail:[email protected]
ISSN0302-9743 e-ISSN1611-3349
ISBN978-3-642-32394-2 e-ISBN978-3-642-32395-9
DOI10.1007/978-3-642-32395-9
SpringerHeidelbergDordrechtLondonNewYork
LibraryofCongressControlNumber:2012943467
CRSubjectClassification(1998):H.3,H.2.8,H.4-5,J.3,J.1
LNCSSublibrary:SL3–InformationSystemsandApplication,incl.Internet/Web
andHCI
©Springer-VerlagBerlinHeidelberg2012
Thisworkissubjecttocopyright.Allrightsarereserved,whetherthewholeorpartofthematerialis
concerned,specificallytherightsoftranslation,reprinting,re-useofillustrations,recitation,broadcasting,
reproductiononmicrofilmsorinanyotherway,andstorageindatabanks.Duplicationofthispublication
orpartsthereofispermittedonlyundertheprovisionsoftheGermanCopyrightLawofSeptember9,1965,
initscurrentversion,andpermissionforusemustalwaysbeobtainedfromSpringer.Violationsareliable
toprosecutionundertheGermanCopyrightLaw.
Theuseofgeneraldescriptivenames,registerednames,trademarks,etc.inthispublicationdoesnotimply,
evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevantprotectivelaws
andregulationsandthereforefreeforgeneraluse.
Typesetting:Camera-readybyauthor,dataconversionbyScientificPublishingServices,Chennai,India
Printedonacid-freepaper
SpringerispartofSpringerScience+BusinessMedia(www.springer.com)
Preface
Biomedicalengineeringandmedicalinformaticsrepresentchallengingandrapidly
growing areas. Applications of information technology in these areas are of
paramount importance. Building on the success of ITBAM 2010 and ITBAM
2011, the aim of the third ITBAM conference was to continue bringing to-
getherscientists,researchers,andpractitionersfromdifferentdisciplines,namely,
from mathematics, computer science, bioinformatics, biomedical engineering,
medicine,biology,anddifferentfieldsoflifesciences,sothattheycanpresentand
discusstheirresearchresultsinbioinformaticsandmedicalinformatics.Wehope
that ITBAM will always serve as a platform for fruitful discussions between all
attendees, where participants can exchange their recent results, identify future
directions and challenges, initiate possible collaborative research, and develop
common languages for solving problems in the realm of biomedical engineering,
bioinformatics, and medical informatics.
The importance of computer-aided diagnosis and therapy continues to draw
attention worldwide and has laid the foundations for modern medicine with
excellent potential for promising applications in a variety of fields, such as,
telemedicine, Web-based healthcare, analysis of genetic information and per-
sonalized medicine. Following a thorough peer-review process, we selected 12
longpapersandthreeshortpapersforthethirdannualITBAMconference.The
OrganizingCommittee would like to thank the reviewers for their excellent job.
The articles can be found in the proceedings and are divided into the follow-
ingsections:MedicalDataMiningandInformationRetrieval;MetadataModels,
Prediction,andMobileApplications;SystemsBiologyandDataMininginBioin-
formatics.The papers show how broadthe spectrum of topics in applications of
information technology to biomedical engineering and medical informatics is.
The editors would like to thank all the participants for their high-quality
contributions and Springer for publishing the proceedings of this conference.
Once again, our special thanks go to Gabriela Wagner for her hard work on
various aspects of this event.
June 2012 Christian Bo¨hm
Sami Khuri
Lenka Lhotska
M. Elena Renda
Organization
General Chair
Christian Bo¨hm University of Munich, Germany
Conference Program Chairs
Sami Khuri San Jos´e State University, USA
Lenka Lhotska Czech Technical University Prague,
Czech Republic
M. Elena Renda IIT - CNR, Pisa, Italy
Program Committee
Werner Aigner FAW
Fuat Akal Functional Genomics Center Zurich,
Switzerland
Tatsuya Akutsu Kyoto University, Japan
Andreas Albrecht Queen’s University Belfast, UK
Lijo Anto Manjaly Antony CentreforBioinformatics,UniversityofKerala,
India
Rub´en Arman˜anzas Arnedillo University of the Basque Country, Spain
Peter Baumann Jacobs University Bremen, Germany
Balaram Bhattacharyya Visva-Bharati University, India
Christian Blaschke Bioalma Madrid, Spain
Andreas M. Boehm Rudolf Virchow Center for Experimental
Biomedicine, Germany
Veselka Boeva Technical University of Plovdiv, Bulgaria
Gianluca Bontempi Universit´e Libre de Bruxelles, Belgium
Roberta Bosotti Nerviano Medical Science s.r.l., Italy
Rita Casadio University of Bologna, Italy
So`nia Casillas Universitat Auto`noma de Barcelona,Spain
Kun-Mao Chao National Taiwan University
Vaclav Chudacek Czech Technical University in Prague,
Czech Republic
Coral del Val Mun˜oz University of Granada, Spain
Hans-Dieter Ehrich Technical University of Braunschweig,
Germany
Mourad Elloumi University of Tunis, Tunisia
Maria Federico University of Modena and Reggio Emilia, Italy
Pedro Fernandes Inst.Gulbenkian de Ciˆencia, Portugal
VIII Organization
Christoph M. Friedrich University of Applied Sciences Dortmund,
Germany
Xiangchao Gan University of Oxford, UK
Alejandro Giorgetti University of Verona, Italy
Alireza Hadj Khodabakhshi Simon Fraser University, Canada
Volker Heun Ludwig-Maximilians-Universita¨tMu¨nchen,
Germany
Chun-Hsi Huang University of Connecticut, USA
Lars Kaderali University of Technology Dresden, Germany
Alastair Kerr University of Edinburgh, UK
Michal Kra´tky´ Technical University of Ostrava,
Czech Republic
Vaclav Kremen Czech Technical University in Prague,
Czech Republic
Josef Ku¨ng University of Linz, Austria
Gorka Lasso CICbioGUNE, Derio, Spain
Roger Marshall Plymouth State University, USA
Elio Masciari ICAR-CNR, Universit`a della Calabria, Italy
Henning Mersch RWTH Aachen University, Germany
Aleksandar Milosavljevic Baylor College of Medicine, USA
Jean-Christophe Nebel Kingston University, London, UK
Vit Novacek NationalUniversity ofIreland,Galway,Ireland
Nadia Pisanti University of Pisa, Italy
Cinzia Pizzi Universit`a degli Studi di Padova, Italy
Clara Pizzuti Institute for HighPerformanceComputing and
Networking (ICAR)-National Research
Council(CNR), Italy
Meikel Poess Oracle Corporation, Redwood Shores, CA,
USA
Nicole Radde Universita¨t Stuttgart, Germany
Stefano Rovetta University of Genova, Italy
Cristina Rubio-Escudero University of Seville, Spain
Nick Sahinidis Carnegie Mellon University, USA
Roberto Santana UniversityoftheBasqueCountry(UPV/EHU),
Spain
Kristan Schneider University of Vienna, Austria
Kathleen Steinhofel King’s College London, UK
A Min Tjoa Vienna University of Technology, Austria
Paul van der Vet University of Twente, The Netherlands
Roland R. Wagner University of Linz, Austria
Viacheslav Wolfengagen Institute JurInfoR-MSU, Russia
Borys Wrobel Polish Academy of Sciences, Poland
Filip Zavoral Charles University in Prague, Czech Republic
Songmao Zhang Chinese Academy of Sciences, China
Qiang Zhu The University of Michigan, USA
Frank Gerrit Zoellner University of Heidelberg, Germany
Table of Contents
Session 1
Intelligent Data Acquisition and Scoring System for Intensive
Medicine........................................................ 1
Filipe Portela, Manuel Filipe Santos, Jos´e Machado, A´lvaro Silva,
Fernando Rua, and Ant´onio Abelha
Data Mining in the Study of the Chronic Obstructive Pulmonary
Disease ......................................................... 16
Maribel Yasmina Santos, Jorge Cruz, and Artur Teles de Arau´jo
Practical Problems and Solutions in Hospital Information System Data
Mining ......................................................... 31
Miroslav Bursa, Lenka Lhotska, Vaclav Chudacek, Jiri Spilka,
Petr Janku, and Martin Huser
Session 2
Using Generic Meta-Data-Models for Clustering Medical Data ......... 40
Dominic Girardi, Michael Giretzlehner, and Josef Ku¨ng
A Mobile Based Authorization Mechanism for Patient Managed Role
Based Access Control............................................. 54
Ca´tia Santos-Pereira, Alexandre B. Augusto, Manuel E. Correia,
Ana Ferreira, and Ricardo Cruz-Correia
Care@HOME: A Mobile Monitoring System for Patient Treatment and
Blood Pressure Tracking .......................................... 69
Mersini Paschou, Efrosini Sourla, George Basagiannis,
Evangelos Sakkopoulos, and Athanasios Tsakalidis
Session 3
An Integrative Clustering Approach Combining Particle Swarm
Optimization and Formal Concept Analysis ......................... 84
Anna Hristoskova, Veselka Boeva, and Elena Tsiporkova
Link Prediction Approaches for Disease Networks .................... 99
Francesco Folino and Clara Pizzuti
X Table of Contents
Toward a Semantic Framework for the Querying, Mining and
Visualization of Cancer Microenvironment Data ..................... 109
Michelangelo Ceci, Fabio Fumarola, Pietro Hiram Guzzi,
Federica Mandreoli, Riccardo Martoglia, Elio Masciari,
Massimo Mecella, and Wilma Penzo
Session 4
Argumentation to Represent and Reason over Biological Systems ...... 124
Adam Wyner, Luke Riley, Robert Hoehndorf, and Samuel Croset
The Use of Design Specificity in Standardized Mean Difference for
Analysis of High throughput RNA Interference Screens ............... 139
Karol Kozak
Toward a Translational Medicine Approach for Hypertrophic
Cardiomyopathy ................................................. 151
Catia M. Machado, Francisco M. Couto, Alexandra R. Fernandes,
Susana Santos, and Ana T. Freitas
Poster Session
Computational Sensemaking on Examples of Knowledge Discovery
from Neuroscience Data: Towards Enhancing Stroke Rehabilitation..... 166
Andreas Holzinger, Reinhold Scherer, Martin Seeber,
Johanna Wagner, and Gernot Mu¨ller-Putz
The Database of the CardiovascularSystem Related Signals........... 169
Jan Havl´ık, Lucie Kuˇcerova´, Imrich Kohu´t, Jan Dvoˇra´k, and
Vratislav Fabi´an
Patient Monitoring Using Bioimpedance Signal ...................... 171
Jan Havl´ık, Ondˇrej Fousek, and Miroslav Loˇzek
Author Index.................................................. 173
Intelligent Data Acquisition
and Scoring System for Intensive Medicine
Filipe Portela1, Manuel Filipe Santos1, José Machado2,
Álvaro Silva3, Fernando Rua3, and António Abelha2
1 Centro Algoritmi, University of Minho, Guimarães, Portugal
{cfp,mfs}@dsi.uminho.pt
2 CCTC, University of Minho, Braga, Portugal
{jmac,abelha}@di.uminho.pt
3 Serviço de Cuidados Intensivos, Centro Hospitalar do Porto, Hospital Santo António, Portugal
[email protected]
[email protected]
Abstract. In a critical area as is Intensive Medicine, the existence of systems to
support the clinical decision is mandatory. These systems should ensure a set of
data to evaluate medical scores like is SAPS, SOFA and GLASGOW. The
value of these scores gives the doctors the ability to understand the real
condition of the patient and provides a mean to improve their decisions in order
to choose the best therapy for the patient. Unfortunately, almost all of the
required data to obtain these scores are recorded on paper and rarely are stored
electronically. Doctors recognize this as an important limitation in the Intensive
Care Units. This paper presents an intelligent system to obtain the data,
calculate the scores and disseminate the results in an online, automatic,
continuous and pervasive way. The major features of the system are detailed
and discussed. A preliminary assessment of the system is also provided.
Keywords: Intensive Medicine Scores, Real Time, Pervasive System, Scoring
System, SAPS, SOFA, GLASGOW.
1 Introduction
During the last three decades, several physiological-based prognostic models have
emerged [1]. In 1980, the severity scoring systems were introduced in the Intensive Care
Units (ICUs) [2]. Intensive-care medicine score systems serve to quantify the severity
of diseases and to characterize patient groups on the basis of objective criteria [1].
The scores describe patient severity by adding up points. As main objectives, they:
assess the prognosis; establish the amount of treatment required; provide information
on the prognosis of patients; indicate the efficacy of therapeutic interventions; and
serve for the stratification in clinical studies and workload [2], helping doctors in the
decision process. In the ICU a high number of scoring systems are used that can be
grouped in: diseases, patient and universally mortality prediction.
This work has been developed in the context of INTCare research project [3], an
intelligent decision support system that makes use of online learning to predict the
C. Böhm et al. (Eds.): ITBAM 2012, LNCS 7451, pp. 1–15, 2012.
© Springer-Verlag Berlin Heidelberg 2012
2 F. Portela et al.
organ failure and the outcome of the ICU patients. The work developed was only
focused on the scores that have variables that are used by Decision Support System,
i.e., SAPS, SOFA and Glasgow. In the context of INTCare, a new set of data had to
be acquired in order to induce Data Mining (DM) models able to predict the organ
failure and the outcome of the patients. These scores rarely were stored in an
electronic way. As a normal procedure, the nurses / doctors calculate these scores by
consulting the patient’s bed side monitors, interpreting the lab results and reading
admission documents in an offline mode. The existence of multiple data sources for
each organic system [4] difficult the evaluation of the variables by the human and,
consequently, can delay / interfere negatively in the decision making process.
For the development of INTCare system this situation was unaffordable. The
inexistence of all data in an electronic mode and in real time made impossible the
construction of prediction models. Those limitations dictated the development of a
completely new scoring system to collect the data and to score the measures in real-
time. A lot of research has been done to understand how it would be possible to
acquire and prepare the necessary data. An intelligent agent based approach has been
followed to perform crucial tasks such as the automatic data acquisition and the online
scoring. The main goal of the project was the concentration of the decision support
tasks in a single platform.
According to Keegan [1] there are several limitations inherent to the ICU
prognostic models: i) errors in data collection and data entry, flaws in development
and validation of the models; ii) variables used to make predictions may not be easily
measured; and some laboratory values may not be routinely obtained. The lack of
standardization in obtaining values leads to missing data and to the fault of important
prognostic variables, compromising the performance of the models [5]. The empirical
experience accumulated in this field of acting allowed the development of a system
able to overcome the limitations described above. This system has been deployed in
the ICU of the Centro Hospitalar do Porto (CHP), Porto, Portugal.
This paper presents an intelligent scoring system to feed DM models as a way to
predict the organ failure and the outcome of the ICU patients. Chapter one introduces
the problematic and the subject, the second chapter makes an overview of the
situation and explains the main concepts. Chapter three present the data manipulation
process. Chapters four and five will present the scoring system and the results
achieved. The preliminary results of a study on the technological acceptance are
presented. Finally, some conclusions will be done about the work and the future work.
2 Background
It is common sense that in the ICU a set of clinical measures should be used regularly.
Many of the scoring processes are executed manually and require a high level of
human intervention. Currently there are systems able to collect all data produced
during the day and execute some scoring. An example of this is the system presented
by Shabot [6] where “Three measures of severity of illness are automatically
calculated for each adult ICU patient on admission and again daily”. When the scores
are calculated manually the value considered are not the worst among the measured
values but the worst value registered by someone. This configures a major limitation.
