Transcript InfoDayZagrebSerbia

M. Rakic, S. Nektarijevic, I. Milinkovic, G. Rakocevic,
M. Bumbasirevic, V. Milutinovic, V. Lekovic (SRB)
with
L. Luic (CRO) + M. Rudolf (SLO)
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Our Research Focus: 5.3.b (i+iii)
Development of ICT tools, services and specialized infrastructure for the biomedical researchers to support at least two of the following three activities: i)
to share data and knowledge needed for a new integrative research approach
in medicine (biomedical informatics), ii) to share or jointly develop multiscale
models and simulators, iii) to create collaborative environments supporting this
highly multidisciplinary field. When necessary, computing power and data
management could be sought through access to existing advanced grid
infrastructures as well as high performance computing resources such as the
emerging petascale computing facilities. New tools, services and applications
will also be evaluated on their effectiveness and their ability to interface with
existing medical research infrastructures. Their targeted services will facilitate
the clinical use of computer based organ and disease models as well as
biomedical data. These tools and services will complement and be compatible
with existing methods and standards (terminologies, ontologies, mark-up
languages) like those used by the Network of Excellence –VPH NoE (FP7-ICTcall 2). International Cooperation in this field is encouraged. The objective is to
support at least one IP to be funded under b).
Our Competitive Advantage: Data Mining Infrastructure On Top of All Above
Our approach concentrates on all issues underlined above, plus an added value
of crucial importance: The infrastructure for data mining which enables a set of
hypotheses to be defined and verified. Appropriate PoC implementations with
contents from dentistry (with special emphasis on periodontal medicine) and
orthopedics (with special emphasis on biomedics). Special emphasis research
methodology oriented to rich statistical analyses.
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i (integrative)
iii (collaborative)
Nota Benne:
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ii (interface)
ii (interaction)
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Sharing data:
Infrastructure for institutional networking
Sharing knowledge:
DataMining + SemanticWeb + ConceptModeling
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Example #1: Interaction of periodontitis
+ diabetes mellitus
+ multiple sclerosis ++
Example #2: Interaction of orthopedics
+ risk factors impact
+ therapy success rates ++
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Special emphasis on reusing of infrastructure
developed through former FP projects:
Special emphasis on eliminating the traps
of reusing (six different trap scenaria)
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Tentative list of core participants:
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Digital libraries include hidden knowledge
Digital contents enable hypothesis testing
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Defining risk factors common to periodontitis and investigated diseases. Using the parameters
which are according to contemporary science found to be significant for investigated diseases,
we will screen and link observed data including risk factors, characteristics, and findings
related to patients.
Investigating and defining the influence of periodontitis on the course of diseaseand on
therapy success. By including systemic healthy patients with periodontitis, we will compare the
clinical, immunological, microbiological and biochemical and other defined parameters
between these systemic healthy and patients with MS and DM. Furthermore, by treating
periodontitis of one part of ill patients, and by collecting post treatment specimens, we will
determine the correlation between periodontal inflammation and systemic status.
Using obtained findings for better understanding still insufficiently explained pathogenesis and
in improving the therapy plan.
Contributing to advancing and resolving the problem of three multifactor diseases,
which are extremely wide spread and present in young population thus with great
socioeconomic significance, by observing entire group of potential risk factors and indicators
of disease.
Providing new perspective and ideas to scientists and physicians fighting against these
diseases.
Creating a software trained on data, using most sophisticated contemporary techniques
and chosen based on most recent and modern scientific achievements.
Implementing software for determining the risk of diseases and deterioration worsening
of disease conditions.
Facilitating decisions relating treatment
Helping in forecasting
Improving knowledge
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Implementation
Dissemination
Analysis
Beyond
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Collecting and tracking of risk factors
for about 100 different use cases
Implementing the system and the procedures
in 10 different medical institutions
Data sharing
Knowledge mining (added value)
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TBD
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Objective 1: To generate use cases for hypotases testing
(patient groups and problem types),
based on previous medical research experiences
of the entire consortium
Objective 2: To specify contents and parameters to be tracked
Objective 3: To design infrastructure with elements
of both computig and communications
Objective 4: To develop a PoC and digital content for one specific field,
applicable to a statistically large enough test base
Objective 5: To select the datamining algorithms
for analysis of test results.
Objective 6: To test the demo system in a number of specific
clinical scenaria, in one country (e.g., SRB).
Objective 7: Same as above, in another country (e.g., CRO).
Objective 8: Same as above, in a third country. (e.g., SLO)
Objective 9: Final analysis and creation of recommendations
for clinical practice all over Europe.
Objective 10: Dissemination to centers all over Europe.
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The project can be organized in 11 work packages:
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WP0
WP1
WP2
WP3
WP4
WP5
Project management, RR
Definition of use case scenarios, X
Development of digital content, FRI
Development of system infrastructure, OPTILAB
Development of testing procedures, ETF
Development of datamining algorithms
for analysis of testing results, FHG
WP6 Testing in environment A, SALERNO
WP7 Testing in environment B, FERRARA
WP8 Testing in environment C, KARLSTAD
WP9 Final analysis and preparation of recommendations
for clinical practice all over Europe, BSC
WP10 Dissemination, MAXELER
Specified work package leaders are tentative
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IP
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WANTED:
Creative Partners From the Region
to
perform biomedical research
to prove the concept,
so we can
perform a huge statistical analysis,
and
cover a large plethora of medical fields
in
financially competitive environments
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