Projects

The work implemented in this project identified

The objective of this project is to use well formalized biomedical information, based on widely adopted KOS (e.g. SNOMED CT, ICD, etc.), in order to propose personalized treatments to patients. This objective will be reached by employing existing knowledge representation formalisms to describe the treatment plan and the goals of the treatment, by formally describe the environment (resources and services) related to the treatment, and by proposing intelligent algorithms to adapt the patient treatment plan according to the evolution of the patient health state and the changes in the environment.The adaptation algorithms will be based on autonomic computing which has proving its efficiency in the domain of Web-Sevices Management. SACCOM will propose new dynamic reconfiguration techniques adapted to the medical systems’ needs. The idea is to apply self-configuration method such composing services, orchestration and/or choreography, for the dynamic reconfiguration of medical services/resources in order to manage the execution of treatment plans and provide a personalized treatment to patients.

Information systems that exploit semantic technologies are widely used in many fields these days and are particularly important in the medical and biomedical domains. Currently, institutions that produce medical data rely on these systems to make semantic data explicit in order to promote data sharing and data exchange. However, the medical and biomedical domains are highly dynamic and knowledge is constantly evolving. Models for representing this knowledge such as ontologies, thesauri, terminologies or, more generally, knowledge organization systems (KOS) are at the heart of information systems and thus need to be updated as new terms are defined in order to remain useful. Moreover, due to the great size of the medical domain, multiple KOS are necessary in order to obtain the largest coverage possible. This is why mapping, or cross-referencing between KOS elements, is used. However, as every new evolution in KOS can directly impact existing mappings, new techniques and tools are required to ensure consistency between the cross-referenced KOS. This maintenance must take into account all of the specificities of the medical sub-domain as well as the structure and format of the particular KOS. This highly dynamic nature of KOS impacts the validity of mappings and their maintenance requires a great effort in adaptation and validation. Although this is a critical issue, existing approaches are not intelligent enough to deal with it without recomputing the whole set of mappings each time a new version of KOS is released. Dynamo aims to develop and propose a new method of mapping maintenance. The objective is to provide a tool-supported formal framework that takes into account the characteristics of changes affecting KOS elements and KOS models as well as the nature of the existing mappings in order to automatise the adaptation of mappings that are made invalid by KOS evolution.