@neurIST - chronic disease management through integration of heterogeneous data and computer-interpretable guideline services.

This paper presents an overview of computerised decision support for clinical practice. The concept of computer-interpretable guidelines is introduced in the context of the @neurIST project, which aims at supporting the research and treatment of asymptomatic unruptured cerebral aneurysms by bringing together heterogeneous data, computing and complex processing services. The architecture is generic enough to adapt it to the treatment of other diseases beyond cerebral aneurysms. The paper reviews the generic requirements of the @neurIST system and presents the innovative work in distributing executable clinical guidelines.

Outlook for grid service technologies within the @neurIST eHealth environment.

The aim of the @neurIST project is to create an IT infrastructure for the management of all processes linked to research, diagnosis and treatment development for complex and multi-factorial diseases. The IT infrastructure will be developed for one such disease, cerebral aneurysm and subarachnoid haemorrhage, but its core technologies will be transferable to meet the needs of other medical areas. Since the IT infrastructure for @neurIST will need to encompass data repositories, computational analysis services and information systems handling multi-scale, multi-modal information at distributed sites, the natural basis for the IT infrastructure is a Grid Service middleware. The project will adopt a service-oriented architecture because it aims to provide a system addressing the needs of medical researchers, clinicians and health care specialists (and their IT providers/systems) and medical supplier/consulting industries.

GEMSS: grid-infrastructure for medical service provision.

OBJECTIVES: The European GEMSS Project is concerned with the creation of medical Grid service prototypes and their evaluation in a secure service-oriented infrastructure for distributed on demand/supercomputing. Key aspects of the GEMSS Grid middleware include negotiable QoS support for time-critical service provision, flexible support for business models, and security at all levels in order to ensure privacy of patient data as well as compliance to EU law. METHODS: The GEMSS Grid infrastructure is based on a service-oriented architecture and is being built on top of existing standard Grid and Web technologies. The GEMSS infrastructure offers a generic Grid service provision framework that hides the complexity of transforming existing applications into Grid services. For the development of client-side applications or portals, a pluggable component framework has been developed, providing developers with full control over business processes, service discovery, QoS negotiation, and workflow, while keeping their underlying implementation hidden from view. RESULTS: A first version of the GEMSS Grid infrastructure is operational and has been used for the set-up of a Grid test-bed deploying six medical Grid service prototypes including maxillo-facial surgery simulation, neuro-surgery support, radio-surgery planning, inhaled drug-delivery simulation, cardiovascular simulation and advanced image reconstruction. CONCLUSIONS: The GEMSS Grid infrastructure is based on standard Web Services technology with an anticipated future transition path towards the OGSA standard proposed by the Global Grid Forum. GEMSS demonstrates that the Grid can be used to provide medical practitioners and researchers with access to advanced simulation and image processing services for improved preoperative planning and near real-time surgical support.