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BIOPATTERN AND BIOPROFILE ANALYSIS IN SUPPORT
OF E-HEALTHCARE
E. C. Ifeachor1, M. Zervakis2, D Lowe3 , E. Biganzoli4, J M Fonseca5, S. Van Huffel 6
1
University of Plymouth, UK; 2Telecommunication Systems Institute, Greece, 3University of
Aston, UK, 4Instituto Nazionale Per Lo Studio Cura Dei Tumori, Italy, 5UNINOVA,
Portugal, 6KUL, Belgium.
[email protected] (www.biopattern.org)
Today, the ability to produce vast amounts of bio-data have vastly outstripped our ability to
sensibly make use of the data for decision making. Producers of novel biosensors and probes
assume that the knowledge infrastructure exists to support new sensing technologies, but this
assumption is false. Even the existence of computational technologies such as the Grid is of
limited usefulness unless intelligent algorithms and supporting infrastructure exist to take
advantage of such technologies. In many areas, modern medicine already generates vast amounts
of data which require considerable expertise and time to analyse, interpret and use. Genomicbased research and the drive towards personalised healthcare are providing new information
about the root causes of diseases and how they might develop and treated, but will generate
more data and exacerbate the situation.
New computational intelligence techniques for bio-data analysis will be needed to fully exploit
information from the vast amounts of data generated from various sources (e.g. clinical, biosensors, genomics/proteomics, laboratory, electrophysiology, imaging etc). They will be needed
in future innovative medical systems for a proper analysis and interpretation of data to support
accurate prediction of the onset and progression of major diseases, their diagnosis, treatment and
prognosis. They will make it possible, for example, to search for similarity of data, by data
mining, to classify patterns by neural networks, and to discover new knowledge. In this respect,
advances in computational intelligence techniques for bio-data analysis will play a crucial role in
the delivery and quality of e-healthcare.
BIOPATTERN is a Network of Excellence (NoE) that integrates the research efforts of 31
partners to harness expertise and information in the new field of biopattern and bioprofile
analysis to underpin eHealthcare. A biopattern is the basic information (pattern) that provides
clues about underlying clinical evidence for diagnosis and treatment of diseases. A bioprofile is a
personal dynamic ‘fingerprint’ that fuses together a person’s current and past bio-history,
biopatterns and prognosis. It combines data, analysis and predications of possible susceptibility
to diseases. The 'Grand Vision' of the NoE is to integrate co-operative research aimed at a panEuropean approach to coherent and intelligent analysis of a citizen’s bioprofile; to make the
analysis of this bioprofile remotely accessible to patients and clinicians; and to exploit the
bioprofile information to combat major diseases such as cancer and brain diseases. The idea is to
move away from ‘local solutions to local problems’ and towards ‘European wide solutions to
European problems’.
In the talk, we will provide insight into the future directions on how bioprofiling, using
biomedical information from different levels (e.g. genomics, proteomics, clinical,
electrophysiology, imaging), could be used as a basis for intelligent, decision support tools for
individualised, early detection, prevention and monitoring of the effectiveness of treatment of
major diseases. We will discuss the information and communications technologies required to
support this and the implications for health authorities.
Key words:
Biopattern, bioprofile, computational intelligence, biomedical informatics,
individualized healthcare.