INFORMATYKA
EKONOMICZNA
BUSINESS INFORMATICS
2(32)•2014
Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Wrocław 2014
Redaktor Wydawnictwa: Dorota Pitulec
Redaktor techniczny: Barbara Łopusiewicz
Korektor: Hanna Jurek
Łamanie: Barbara Szłapka
Projekt okładki: Beata Dębska
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The Central and Eastern European Online Library www.ceeol.com,
a także w adnotowanej bibliografii zagadnień ekonomicznych BazEkon http://kangur.uek.krakow.pl/
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Kopiowanie i powielanie w jakiejkolwiek formie
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© Copyright by Uniwersytet Ekonomiczny we Wrocławiu
Wrocław 2014
ISSN 1507-3858
Wersja pierwotna: publikacja drukowana
Druk i oprawa:
EXPOL, P. Rybiński, J. Dąbek, sp.j.
ul. Brzeska 4, 87-800 Włocławek
Spis treści
Wstęp:................................................................................................................ 9
Część 1. Informatyka w organizacji
Zbigniew Antczak: Wpływ narzędzi informatycznych na kierunki ewolucji
funkcji personalnej w przedsiębiorstwach w Polsce w XXI wieku............. Ewa Badzińska: Indywidualizacja rozwiązań ICT w praktyce gospodarczej
na przykładzie start-upów akademickich..................................................... Grzegorz Biziel, Adam Pyka, Tomasz Skalniak, Jan Słowik: Platforma zarządzania usługami jako narzędzie wspierające życie osób starszych........ Iwona Chomiak-Orsa, Michał Flieger: Wykorzystanie technologii informacyjno-komunikacyjnych determinantą doskonalenia komunikacji z interesariuszami w gminach.................................................................................. Małgorzata Furmankiewicz, Anna Sołtysik-Piorunkiewicz, Piotr Ziuziański: Artificial intelligence and multi-agent software for e-health
knowledge management system.................................................................. Małgorzata Furmankiewicz, Anna Sołtysik-Piorunkiewicz, Piotr Ziuziański: Zaawansowane techniki graficznej analizy danych epidemiologicznych na kokpicie menedżerskim........................................................... Wiesława Gryncewicz, Karol Łopaciński: Technologia informacyjna jako
determinanta rozwoju e-usług w sektorze medycznym i rehabilitacyjnym.
Jarosław Jankowski, Maciej Janiak: Zastosowanie modeli wnioskowania
rozmytego w projektowaniu struktury interfejsu systemu rekomendującego.
Jerzy Korczak: Chmura obliczeniowa dla logistyki – projekt LOGICAL...... Krzysztof Kubiak: Przepływy wartości z wykorzystaniem narzędzi ICT
– case study.................................................................................................. Bernard F. Kubiak: Model informacji strategicznej w obsłudze procesów
biznesowych przemysłu turystycznego....................................................... Iwona Małgorzata Kutzner: Wykorzystanie Visual Basic w procesie rekrutacji i selekcji pracowników na przykładzie Instytutu Edukacji Gospodarczej Sp. z o.o. .............................................................................................. Maja Leszczyńska: Analiza i ocena uwarunkowań oraz możliwości wirtualizacji procesów wdrażania i utrzymywania systemów informatycznych..... 13
24
33
41
51
64
78
86
95
106
116
133
156
6
Spis treści
Józef Bohdan Lewoc, Iwona Chomiak-Orsa, Antoni Izworski, Sławomir
Skowroński, Antonina Kieleczawa, Marion Ann Hersh, Peter Kopacek: Optimization of network topology in a CIMM system used in organization management ..................................................................................... Maria Mach-Król: Narzędzia budowy systemu z temporalną bazą wiedzy
wspomagającego twórczość organizacyjną................................................. Adam Nowicki, Bogdan Burkot: Zarys koncepcji doskonalenia procesów
programowych – podejście systemowe....................................................... Maria Pietruszka, Marian Niedźwiedziński: Third dimension of e-commerce............................................................................................................ Cezary Stępniak, Tomasz Turek: Technologiczne uwarunkowania budowy
regionalnej społeczności biznesowej........................................................... Radosław Wójtowicz: Wdrażanie systemów klasy Enterprise Content Management jako złożone przedsięwzięcie informatyczne.................................. Łukasz Żabski: Functions of the integrated computer system of Ministry of
the Treasury within the scope of exercising the owner’s supervision......... 168
179
188
198
213
223
235
Część 2. Dydaktyka
Ewa Badzińska: Potencjał urządzeń mobilnych i gamifikacji w usługach
edukacyjnych............................................................................................... Paweł Chrobak: Wdrażanie infrastruktury VDI w środowisku akademickim
– studium przypadku.................................................................................... Dorota Jelonek, Barbara Łukasik-Makowska: Efekty kształcenia jako
podstawa projektowania programu studiów na kierunku Informatyka ekonomiczna...................................................................................................... Arkadiusz Januszewski: Zastosowanie technologii informatycznych w kształceniu studentów w zakresie controllingu i rachunkowości zarządczej......... Jerzy Korczak, Witold Abramowicz, Jerzy Gołuchowski, Andrzej Kobyliński, Mieczysław Owoc: Wzorcowy program studiów licencjackich
kierunku Informatyka ekononomiczna – koncepcja wstępna...................... Karol Korczak, Konrad Szymański: Wykorzystanie wiedzy z zakresu Informatyki ekonomicznej w procesie modelowania ścieżek kształcenia...... Barbara Łukasik-Makowska, Jerzy Korczak, Paweł Chrobak, Maciej
Bac: Wykorzystanie technologii informacyjnych w procesach wdrażania
Krajowych Ram Kwalifikacji dla Szkolnictwa Wyższego.......................... Karolina Muszyńska, Jakub Swacha: Wykorzystanie narzędzi komunikacji, współpracy i wymiany plików przez studentów kierunków Informatyka i Zarządzanie........................................................................................... Małgorzata Pańkowska: Prezentacja efektów kształcenia w kartach przedmiotów......................................................................................................... 251
262
274
300
311
338
350
365
376
Spis treści
7
Summaries
Part 1. Informatics in organization
Zbigniew Antczak: The influence of information tools on the evolution
trends of hr function in enterprises in Poland in the XXIst century............. Ewa Badzińska: Individualization of ICT solutions in business practice on
the example of academic start-ups............................................................... Grzegorz Biziel, Adam Pyka, Tomasz Skalniak, Jan Słowik: Service management platform as an independent living supporting tool for senior citizens.............................................................................................................. Iwona Chomiak-Orsa, Michał Flieger: ICT technologies as a way to improve communication with stakeholders in local governments .................. Małgorzata Furmankiewicz, Anna Sołtysik-Piorunkiewicz, Piotr Ziuziański: Sztuczna inteligencja i multiagenci oprogramowania w systemie
zarządzania wiedzą w e-zdrowiu................................................................. Małgorzata Furmankiewicz, Anna Sołtysik-Piorunkiewicz, Piotr Ziuziański: Advanced techniques for graphical analysis of epidemiological
data on management dashboard.................................................................... Wiesława Gryncewicz, Karol Łopaciński: Information technology as a determinant of e-services development in medical and rehabilitation sector.. Jarosław Jankowski, Maciej Janiak: Application of fuzzy inference models
in the Web recommending interface design ................................................ Jerzy Korczak: Architecture of computing cloud – LOGICAL project........... Krzysztof Kubiak: Value stream flow using ICT tools – case study .............. Bernard F. Kubiak: Model of strategic information in support of business
processes of the tourism industry ............................................................... Iwona Małgorzata Kutzner: Usage of Visual Basics in the process of recruitment and selection of employees at IEG LLC .................................... Maja Leszczyńska: Analysis and evaluation of determinants and possibilities of virtualization of implementation and maintenance processes of it
systems......................................................................................................... Józef Bohdan Lewoc, Iwona Chomiak-Orsa, Antoni Izworski, Sławomir
Skowroński, Antonina Kieleczawa, Marion Ann Hersh, Peter Kopacek: Optymalizacja topologii sieci w systemach CIMM wykorzystywana
w zarządzaniu organizacjami....................................................................... Maria Mach-Król: Tools for developing a system with temporal knowledge
base to support organizational creativity..................................................... Adam Nowicki, Bogdan Burkot: Draft of a concept for software process improvement − system approach .................................................................... 23
32
40
50
63
77
85
94
105
115
132
155
167
178
187
197
8
Spis treści
Maria Pietruszka, Marian Niedźwiedziński: Trzeci wymiar w e-commerce............................................................................................................ Cezary Stępniak, Tomasz Turek: Technological conditionings of regional
spatial community creation.......................................................................... Radosław Wójtowicz: Implementation of ECM As a complex it project........ Łukasz Żabski: Funkcje zintegrowanego systemu informatycznego Ministerstwa Skarbu Państwa w zakresie sprawowania nadzoru właścicielskiego.. 212
222
234
248
Part 2. Didactics
Ewa Badzińska: Potential of mobile devices and gamification in educational
services........................................................................................................ Paweł Chrobak: Implementation of VDI infrastructure in an academic environment − case study................................................................................... Dorota Jelonek, Barbara Łukasik-Makowska: Learning outcomes as the
base for program of studies design at the business informatics field of
study............................................................................................................. Arkadiusz Januszewski: Application of information technology to managerial accounting and financial controlling at the university-level education.
Jerzy Korczak, Witold Abramowicz, Jerzy Gołuchowski, Andrzej Kobyliński, Mieczysław Owoc: Standard program of bachelor study in
Business Informatics – preliminary concept................................................ Karol Korczak, Konrad Szymański: The use of knowledge of business informatics in the learning pathways modeling process................................. Barbara Łukasik-Makowska, Jerzy Korczak, Paweł Chrobak, Maciej
Bac: USe of it in implementation process of the National Framework of
Qualification Standards for Higher Education............................................ Karolina Muszyńska, Jakub Swacha: Use of communication, collaboration
and file sharing tools by students of information technology and management............................................................................................................. Małgorzata Pańkowska: Learning outcomes presentation in course cards .... 261
273
299
310
337
349
364
375
387
INFORMATYKA EKONOMICZNA
BUSINESS INFORMATICS
2(32) • 2014
ISSN 1507-3858
ałgorzata Furmankiewicz,
M
Anna Sołtysik-Piorunkiewicz, Piotr Ziuziański
University of Economics in Katowice
e-mail: [email protected];
[email protected]; [email protected]
ARTIFICIAL INTELLIGENCE
AND MULTI-AGENT SOFTWARE FOR E-HEALTH
KNOWLEDGE MANAGEMENT SYSTEM
Summary: In this paper, the authors describe and compare the features of examples of the
multi-agent systems (MAS) in e-health. The descriptions of MAS in e-health are presented
in four areas: assistive living application, diagnosis, physical telemonitoring, smart-hospital
and smart-emergency application. The authors divided the e-health MAS due to the areas of
supported knowledge management in e-health: (1) knowledge about the patient: K4CARE,
U-R-SAFE, MyHeart, MobiHealth, (2) knowledge of the presented medical problem: OHDS,
HealthAgents, IHKA, (3) contextual knowledge about the course of the conversation: CASIS,
AID-N, CASCOM, Akogrimo and (4) knowledge of the health organization: ERMA, ­SAPHIRE.
Keywords: artificial intelligence, agent technology, e-health, knowledge management system.
DOI: 10.15611/ie.2014.2.05
1. Introduction
Knowledge is often the basis for the effective utilization of many important resources [Sołtysik-Piorunkiewicz 2013]. In this context, multi-agent software (MAS) may
play an important role in effectuating the knowledge-based view of the e-health organization by enhancing the capability to manage the knowledge it possesses. This
awareness is one of the main reasons for the exponential growth of MAS for knowledge management systems (KMS). KMS are technologies that support knowledge
management in organizations, specifically, knowledge generation, codification, and
transfer [Davenport, Prusak 1998]. Nowadays every knowledge-based organization
is trying to integrate both explicit and tacit knowledge in formal information system
[Turban, Leidner, McLean, Wetherbe 2006]. KMS are implemented in an organization to cope with rapid changes of information using modern information technologies, e.g. intranets with information portals, artificial intelligence and multi-agents
software, data warehouses and business intelligence.
52
Małgorzata Furmankiewicz, Anna Sołtysik-Piorunkiewicz, Piotr Ziuziański
The paper is organized as follows: first the authors present a review on knowledge management processes and systems, and then they show artificial intelligence
and agent technology as a tool for managing the knowledge in e-health organization.
The following section focuses on the e-health multi-agent software; the authors present a comprehensive view of characteristics of this tool and the comparative analysis
of the four case studies (K4CARE, OHDS, MyHeart, CASCOM) in order to identify
various areas of the e-health MAS. In the final section, the authors classify the usage
of the examples of MAS to proper knowledge management processes in an e-health
organization.
2.Knowledge management system
Knowledge management system is dedicated to help an organization to meet its
goals and to increase its effectiveness. The literature review shows that multiple
definitions of knowledge management system have been proposed in the literature,
and debates about this concept have been expressed from a variety of perspectives
and positions.
The knowledge management systems are based on four main phases of knowledge management cycle: knowledge generation, knowledge storage, knowledge distribution and knowledge application. Most life cycles are articulated in four phases
where the first one is a knowledge creation. The second phase corresponds to the organization of knowledge. The third phase uses a different term across the models, but
they all address some mechanism for making knowledge formal. Finally, the fourth
phase concerns the ability to share and use knowledge in the enterprise. Therefore, in
this article, the knowledge development cycle is defined as the process of knowledge
generation, knowledge storage, knowledge distribution and knowledge application
in an e-health organization as a knowledge-based organization. A detailed definition
of these processes will be presented when linking them with the different tools of the
agent functionality that support e-health knowledge management.
In this article the model of multi-agent knowledge management system is based
on [Sołtysik-Piorunkiewicz 2014]:
• knowledge creation about the user,
• knowledge sharing of the presented problem,
• contextual knowledge about the course of the conversation during knowledge
distribution,
• knowledge application in the organization.
3.Artificial intelligence and agent technology
Artificial intelligence, which is regarded as a scientific discipline, emerged after the
introduction of the first computers. Those were ascribed to the skills characteristic of
Artificial intelligence and multi-agent software...
53
intelligent beings, including proving hypotheses, concluding, and games playmaking [Sztuczna inteligencja i elementy…2005]. Currently, the concept of the artificial
intelligence is understood as a branch of IT, whose subject is the study of the rules
governing the so-called intelligent human activities, and the creation of formal models of these behaviours, which in turn leads to the creation of computer programs that
will simulate these behaviours. The above mentioned intelligent behaviours are [Inteligentne systemy… 2009]:
1) perception,
2) learning,
3) recognition,
4) usage of language,
5) symbol manipulation,
6) creativity,
7) solving problems.
Computer programs are used both for experimental and practical purposes, such
as [Inteligentne systemy… 2009]:
1) sounds recognition (speech),
2) recognition of shapes (letters, drawings, photographs),
3) theorem proving,
4) running games (chess),
5) translation from one natural language to another,
6) music composition,
7) formulation of medical diagnoses,
8) expertise formulation.
The notion “artificial intelligence“ (AI) was suggested in 1956 by John McCarthy from Massachuset Institute of Technology as the subject of a conference in
Dartmouth [Owoc 2006]. The aim of the conference was to summarize and intensify
further research on “thinking machines”. The conference was a success. After that
the work on projects that concerned the field of artificial intelligence was greatly
intensified.
The concept of artificial intelligence cannot be precisely defined. One can find
many definitions of artificial intelligence in the literature [Wstęp do… 2011]. Nevertheless, it is worth mentioning the first definition of artificial intelligence, which was
introduced by John McCarthy: “[...] the construction of the machines, which can be
said to be similar to the human manifestations of intelligence“ [Sztuczna inteligencja… 2005].
Definitions, which appeared later, can be divided into four categories, taking
into account two main criteria. One group of the definitions refers to the process of
thinking and reasoning, while others take into account the behavioural factor (called
behaviour). The second distinction between the definition of artificial intelligence
takes into account the category of success. The examples of the definitions used in
various categories were presented in Figure 1.
54
Małgorzata Furmankiewicz, Anna Sołtysik-Piorunkiewicz, Piotr Ziuziański
Figure 1. Organization of the artificial intelligence definitions into 4 categories
Source: own study based on [Sztuczna inteligencja… 2005].
One can distinguish two different approaches to artificial intelligence. The first
one referred to as weak AI assumes that the computer allows to formulate and test
specific hypotheses concerning the brain [Inteligentne systemy…. 2009]. The second approach, named strong artificial intelligence extends much more radical claims
about AI. The followers of strong AI believe that a properly programmed computer
is not only a model of brain but a brain as such [Wstęp do… 2011]. The origins
of modern artificial intelligence can be traced to 1943, when McCulloch and Pitts
proposed the neural network architecture to create intelligence. Seven years later,
in 1950, A. Turing proposed the “intelligence test“ [Sztuczna inteligencja… 2005].
Recently agent technology has become one of the most important areas of Artificial Intelligence (AI) research. An agent is an entity capable of performing some
tasks and helping a human user in that way. Agents can be biologic (for example people), computational (software agents) or robotic. Software agents could be defined as
a computer program that aim is carrying out some task on behalf of a user. The most
important properties of agents are: intelligence, autonomy, cooperation and ability
to learn [Coppin 2004].
Agent software which is combined into one system is named multi-agent system
(MAS). It can be a very powerful tool. The following statements are characteristic in
multi-agent systems [Coppin 2004]:
1) each agent disposes not complete information that is why an agent is not capable to solve the entire problem on its own,
2) only combined agents can solve a problem,
3) system does not use any centralized mechanism for solving a problem.
55
Artificial intelligence and multi-agent software...
The main aim of agents is observing knowledge base in the current situation context and supporting the process of making a decision concerning an action by experts
in their domain. The last step is executing that action on the environment [Cortés,
Annicchiarico, Urdiales 2008].
Agents are often confused with expert systems. This results from the fact that
those two entities have a knowledge base. A basic difference between them is how
they use a knowledge base. Experts systems use logic in every situation, whereas
agents act more like people: more important is to find result and accept some level
of its probability than to find a perfect result [Henderson 2007].
4. Multi-agent software in e-health
There is a diversity of areas in medical industry and health care systems that could
benefit from systems based on agent technology (especially MAS) [Cortés, Annicchiarico, Urdiales 2008]:
1) systems diagnosing diseases,
2) systems that recommend treatment,
3) patient history examination systems,
4) the support of palliative care units.
The descriptions of multi-agent systems in e-health are presented in table 1
[Bergenti, Poggi 2009], [Cortés, Annicchiarico, Urdiales 2008], [Furmankiewicz,
Sołtysik-Piorunkiewicz, Ziuziański 2014], [K4CARE], [Peleg, Broens, González-Ferrer, Shalom 2013], [U-R-SAFE], [Ziuziański, Furmankiewicz, Sołtysik-Piorunkiewicz 2014] in four areas:
1) assistive living application: CASIS, K4CARE,
2) diagnosis: IHKA, OHDS, HealthAgents,
3) physical telemonitoring: MobiHealth, U-R-SAFE, AID-N, MyHearth,
SAPHIRE,
4) smart-hospital, and smart-emergency application: ERMA, Akogrimo, CASCOM.
Table 1. Examples of multi-agent systems
Area
Name
Description
1
2
3
CASIS
Supplying context-aware healthcare services to the elderly
Assistive
Context-Aware Service resident in the intelligent space.
Living
Applications Integration System
K4CARE (2006)
Project combining healthcare and ICT experiences to
develop, apply, and validate a knowledge-based healthcare
model for assistance to patients living at home (elderly, the
disabled persons, and the patients with chronic diseases).
56
Małgorzata Furmankiewicz, Anna Sołtysik-Piorunkiewicz, Piotr Ziuziański
Table 1, cont.
1
Diagnosis
Physical
Tele­
monitoring
2
3
IHKA
Intelligent Healthcare
Knowledge Assistant
Healthcare knowledge procurement system based on six
agent types for dynamic knowledge gathering, filtering,
adaptation and acquisition from a healthcare enterprise
memory.
OHDS
Ontology based
Holonic Diagnostic
System
System supporting doctors in the diagnostic and treatment,
and overseeing processes of the evolution of new
epidemics. System is based on the exploration of all data
pertinent to each case and on the scientific data contained
in various professional databases
HealthAgents
Research project with the goal of improving the classification of brain tumours distributed network of local databases.
MobiHealth
The main goal of it is telemonitoring of patients at home
by monitoring, storage and transmission of vital signs data
coming from the patient body area network (BAN).
U-R-SAFE
Universal Remote
Signal Acquisition For
hEalth
Research project with the goal of realizing a
telemonitoring environment for elderly people and patients
with chronic diseases.
AID-N
Advanced Health and
Disaster Aid Network
Light-weight wireless medical system for efficiently
gathered and distributed information on the vital signs and
locations of patients.
MyHeart
Research project whose focus was on preventing
cardiovascular diseases using sensors integrated in clothing
to monitor heart activity.
SAPHIRE
Research project whose goal was monitoring chronic
diseases both at hospital and at home using a semantic
infrastructure.
ERMA
SmartEmergency
Hospital,
Medical Assistant
SmartEmergency
Applications
The main aim of ERMA was providing meaningful
diagnoses and intervention suggestions to the healthcare
team acting on behalf of the patient in the cases of
emergency trauma with particular emphasis on types of
shock and stabilization of arterial blood gases.
Akogrimo
Research project whose main goal is the integration of the
next generation grids with the next generation networks.
CASCOM
Context-Aware
Health-Care Service
Co-ordination in
Mobile Computing
Environments
The main aim of the project is to implement, validate, and
try a value-added supportive infrastructure for Semantic
Web based business application services across mobile and
fixed networks.
Source:own study based on [Bergenti, Poggi 2009], [Cortés, Annicchiarico, Urdiales 2008], [Furmankiewicz, Sołtysik-Piorunkiewicz, Ziuziański 2014], [K4CARE], [Peleg, Broens, González-Ferrer, Shalom 2013], [U-R-SAFE], [Ziuziański, Furmankiewicz, Sołtysik-Piorunkiewicz 2014].
57
Artificial intelligence and multi-agent software...
One of the examples of agent using in e-health is K4CARE, which is used in
the assistive living area. K4CARE is a specific targeted research project, which was
realized by thirteen academic and industrial institutions from seven countries over
three years [K4CARE]. Table 2 presents institutions involved in the project.
Table 2. Institutions involved K4CARE
Number
1.
Country
Czech Republic
2.
Institution
Ceske Vysoke Uceni Technicke v Praze
Vseobecna Fakultni Nemocnice v Praze
3.
Germany
European Research and Project Office GmbH
4.
Hungary
Computer and Automation Research Institute of the Hungarian
Academy of Sciences
5.
6.
Szent Janos Hospital
Italy
Azienda Unita Sanitaria Locale Roma B
7.
Universita degli Studi di Perugia
8.
Telecom Italia Spa
9.
Comune di Pollenza
10.
Santa Lucia Institute
11.
Romania
Fundatia Ana Aslan International
12.
Spain
Universidad Rovira I Virgili
13.
United Kingdom
The Research Institute for the Care of the Elderly
Source: own study based on [K4CARE].
K4CARE is an answer for human health needs in modern societies. The main
receivers of agent are [Bergenti, Poggi 2009]:
1) older people,
2) people with disabilities,
3) people with chronic diseases.
Many of those people need professional care for 24 hours for their whole life.
K4CARE connects healthcare and information and communications technology
(ICT) experiences of several western and eastern European Union countries to create, implement, and validate a knowledge-based healthcare model for the professional assistance to patients at home. The main objectives of K4CARE agent are
presented in Figure 2.
As an example of multi-agent system in diagnosis area OHDS has been chosen.
OHDS (Ontology based Holonic Diagnostic System) combines the advantages of the
holonic paradigm with multi-agent system technology and ontology design, in order
to realize a highly reliable, flexible, scalable, adaptive, and robust diagnostic system
for diseases [Hadzic, Ulieru, Chang 2014]. The main task of OHDS is to support
58
Małgorzata Furmankiewicz, Anna Sołtysik-Piorunkiewicz, Piotr Ziuziański
Figure 2. The main objective of K4CARE agent
Source: own study based on [K4CARE].
the doctors in the diagnostic, treatment and supervision processes of the evolution
of new epidemics. This is possible based on the exploration of all data important
to each case and on the scientific data contained in different professional databases
[Bergenti, Poggi 2009].
MyHeart has been chosen to represent a multi-agent system in physical telemonitoring area. MyHeart is biomedical and healthcare research within the European
Union. It started in 2003 and was run until 2010. Philips Research was the main contributor of MyHeart. As the name suggests the project was related to heart or rather
to heart disease (Cardiovascular disease, CVD). This project was very important
because this kind of diseases are the prominent reason of death in the western world
[Sinadinakis 2011]. MyHeart project identified key product ideas that could help to
prevent and to manage CVD, which is presented in Figure 3 [MyHeart 2014].
Technology used in mentioned areas is named intelligent biomedical clothes
(IBC). It is connected with wireless-based telemetry and user interaction systems
and it uses embedded textile sensors. One of the most important developed technologies in MyHeart relates to the signal processing algorithms. It is necessary to extract
electrocardiography (ECG) data from the electrodes located in vest and bed sensors
[Sinadinakis 2011] [MyHeart 2014]. MyHeart is solution delivering of following
opportunities [Sinadinakis 2011]:
1) monitoring vital signs of inhabitants,
2) diagnosis making,
3) trend detecting,
4) reacting on all above.
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Artificial intelligence and multi-agent software...
Acvity Coach
Maximizing the enjoyment and
health benefits of regular
exercise. Targeted primarily at
healthy individuals.
Neuro Rehab
Improving and shortening the
rehabilitaon period through
physical and mental exercises,
targeted primarily at stroke
vicms.
MyHeart product
concepts for CVD
prevenon and
management
Take Care
Assessment and reducon of
the risk factors for CVD through
vital body signs monitoring,
lifestyle coaching and
movaon for people who are
at risk of developing CVD.
Heart Failure Management
Improving quality of life and life
expectancy for heart failure
paents by early detecon of
deterioraon in their condion
(decompensaon) and
improved paent management.
Figure 3. Key product ideas helping to prevent and manage CVD identified by MyHeart project
Source: own study based on [MyHeart].
Agent
technology
Context and
Situaon
Awareness
Mobile
technology
Cascom
Semanc
Web Service
Coordinaon
Intelligent
Peer-to-Peer
Fig. 4. Used technologies in CASCOM
Source: own study based on [Bergenti, Poggi 2008].
As an example of smart-hospital, smart-emergency applications CASCOM have
been chosen. It is mainly a compilation of three growing up technologies: multiagent systems, semantic Web and services and Peer-to-Peer (P2P) [Bergenti, Poggi
2008]. More accurate list of the technology used is presented in Figure 4 [Schumacher, Helin 2008].
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Małgorzata Furmankiewicz, Anna Sołtysik-Piorunkiewicz, Piotr Ziuziański
The main aim of CASCOM is to develop, validate, and trial supportive infrastructure for business application services for mobile workers and users across the
networks (fixed and mobile) [Cascom 2014]. The authors of the project have presented an e-health scenario showing possibilities of this solution touching one of the
biggest challenges in emergency healthcare: making a decision on the treatment of
patients without their medical history [Bergenti, Poggi 2008].
Another example of HealthAgents system is based on multi-agent technology and designed for diagnosing and forecasting brain tumors. Other example is
SAPHIRE that is a multi-agent system for monitoring remote healthcare through
electronic clinical guidelines [Cortés, Annicchiarico, Urdiales 2008].
5.The study of multi-agent software in e-health knowledge
management systems
The model of e-health knowledge management systems is based on some criteria the
agent software could support:
1) knowledge about the user,
2) knowledge of the presented problem,
3) contextual knowledge about the course of the conversation,
4) knowledge of the organization [Sołtysik-Piorunkiewicz 2014].
The study of MAS is based on four agent functionalities in e-health knowledge
management systems:
1) knowledge about the patient,
2) knowledge of the presented medical problem,
3) contextual knowledge about the course of the conversation in e-health,
4) knowledge of the e-health organization.
The authors studied 13 different MAS dedicated for e-health: 2 examples of
assistive living applications of MAS, 3 examples of diagnosis of MAS, 5 examples
of physical telemonitoring of MAS, and 3 examples of Smart-Hospital, Smart-Emergency Applications of MAS. After the comparative study of different examples of
MAS the authors classified them based on agent functionality in e-health knowledge
management system.
The summary of the study is shown in table 3.
6. Conclusions
The features of the agent functionality in knowledge management e-health systems
are divided into four areas. The results of the study show the following groups of
e-health MAS: (1) knowledge about the patient: K4CARE, U-R-SAFE, MyHeart,
MobiHealth, (2) knowledge of the presented medical problem: OHDS, HealthAgents, IHKA, (3) contextual knowledge about the course of the conversation: CASIS,
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Artificial intelligence and multi-agent software...
Table 3. Agent functionality in e-health knowledge management system
Multi-agents systems
Area
Name
Agent functionality in e-health knowledge management systems
knowledge
about the
patient
knowledge of
the presented
medical
problem
contextual
knowledge
about the
course of the
conversation
Assistive Living
Applications
K4CARE
X
Physical
Telemonitoring
U-R-SAFE
X
Physical
Telemonitoring
MyHeart
X
Physical
Telemonitoring
MobiHealth
X
Diagnosis
OHDS
X
Diagnosis
HealthAgents
X
Diagnosis
IHKA
X
Assistive Living
Applications
CASIS
X
Physical
Telemonitoring
AID-N
X
Smart-Hospital,
CASCOM
Smart-Emergency Akogrimo
Applications
ERMA
Physical
Telemonitoring
SAPHIRE
knowledge
of the health
organization
X
X
X
X
Source: own study.
AID-N, CASCOM, Akogrimo and (4) knowledge of the health organization: ERMA,
SAPHIRE. The future research will find the features of usability aspect of MAS for
knowledge management system in e-health organization.
References
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Workshop Dagli Oggetti agli Agenti, Palermo.
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10th International Workshop on Objects and Agents, Rimini.
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Małgorzata Furmankiewicz, Anna Sołtysik-Piorunkiewicz, Piotr Ziuziański
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Artificial intelligence and multi-agent software...
63
SZTUCZNA INTELIGENCJA
I MULTIAGENCI OPROGRAMOWANIA
W SYSTEMIE ZARZĄDZANIA WIEDZĄ W E-ZDROWIU
Streszczenie: W niniejszym artykule autorzy opisują i porównują cechy przykładowych
systemów wieloagentowych w e-zdrowiu. Systemy wieloagentowe w e-zdrowiu zostały
przedstawione w czterech obszarach: aplikacje wspomagające życie pacjenta, diagnostyka
medyczna, telemonitoring oraz inteligentne szpitale. Autorzy podzielili systemy wieloagentowe e-zdrowia ze względu na obszary zarządzania wiedzą wspierane w e-zdrowiu: (1) wiedza
o pacjencie: K4CARE, UR-SAFE, MyHeart, MobiHealth, (2) znajomość prezentowanego
problemu medycznego: OHDS, HealthAgents, IHKA, (3) wiedza kontekstowa z przebiegu
rozmowy z pacjentem: CASIS, AID-N, CASCOM, Akogrimo i (4) znajomość organizacji
ochrony zdrowia: ERMA, SAPHIRE.
Słowa kluczowe: sztuczna inteligencja, technologie agentowe, e-zdrowie, system zarządzania wiedzą.