ASSIST

The main objective of ASSIST is to facilitate the research for cervical cancer through a system that will virtually unify multiple patient record repositories, physically located in different medical centers/hospitals. Innovative, knowledge-intensive semantic modelling, fuzzy inferencing and data mining techniques will be developed to this end. ASSIST’s inference engine will translate medical concepts into syntactic values that legacy systems may perceive and support the process of evaluating medical hypotheses and contacting association studies.

The unification of participating archives, containing both clinical and genetic data, into a single medical knowledge source will increase research flexibility by allowing the formation of study groups “on demand” and by recycling patient records in new studies.

This approach is expected to benefit the study of gynecological neoplasias, whose evaluation requires long-term studies including referral to patients’ antecedents and descendants.

ASSIST will incorporate a quality assurance mechanism to resolve security and ethical issues.

Consortium

Informatics and Telematics Institute (Greece) (Coordinator)

RAMIT (Belgium)

Charite Universitatsmedizin Berlin, Gynakologie mit Hochschulambulanz (Germany)

SWORD Technologies S.A. (Luxemburg)

Aristotle University Of Thessaloniki (Greece)

Birkbeck College, University of London (UK)

Benchmark Performance Ltd (UK)

Institute of Communication and Computer Systems (Greece)

EbioIntel S.L. (Spain)

Pouliadis Associates (Greece)

CUSTODIX (Belgium)