ASsociation Studies assisted by Inference and Semantic Technologies
|Title||ASsociation Studies assisted by Inference and Semantic Technologies|
|Funding Source||European Commission – IST program|
|Amount||€4,170,154 (our part is ~€789,480)|
Cervical cancer is the second most common cancer worldwide with 60000 new cases and 30000 deaths each year in Europe alone, despite a significant progress in early diagnosis and treatment. Recent trends in medical research combine genetic with clinical data and perform association studies among environmental agents, virus characteristics and genetic attributes, in order to identify new markers of risk, diagnosis and prognosis. While the number of studies describing phenotype-genotype associations is rapidly increasing, progress is hindered by the segmentation of various efforts and their corresponding datasets. 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. The consortium comprises four IT research partners, four developers, and three research hospitals. The gynecological clinics in these hospitals, already owning a sizeable amount of clinical and genetic data, will attempt to uncover relations between HPV, patient habits and patient genotype.