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REACTION is affilliated with these programs and organisations:
REACTION is delivering better and more efficient healthcare services in Europe, thus supporting the Commissions activities in ICT for Health: eHealth.
The REACTION platform allows for the creation of inclusive applications with accessibility for all. The project supports the Commissions campaign: eInclusion - be part of it!
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The REACTION project is a 4-year project started in 2010. It is partly funded by the European Commission under the 7th Framework Programme in the area of Personal Health Systems under Grant Agreement no. 248590
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Web Links: EU programmes
| Personal health systems | |
| ICTs offer the possibility of a new generation of lightweight monitoring systems which a patient can wear while going about their daily business, or which can be carried around easily and used regularly. Such new systems and tools can now provide much more reliable data on multiple parameters, and transmit them to remote locations, so that medical professionals can make better decisions on treatment without having to meet the patients face-to-face.  In FP7, the Commission gives financial support for projects which seek to develop advanced ICT applications to develop Personal Health Systems.  | 
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| Date Added: 18-05-2010 | Visits: 2749 | 
| Risk assessment and patient safety | |
| ICT has considerable potential to improve risk assessment in healthcare.  It enables the gathering and processing of large amounts of data helping policy-makers allocate resources according to healthcare needs. At the level of individual patients, ICT can be used to guide treatment decisions minimise the possibility of adverse side effects and complications.  In FP7, the Commission aims to supports projects which seek to develop advanced ICT applications to improve risk assessment and patient safety.  | 
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| Date Added: 18-05-2010 | Visits: 2786 | 
| Virtual physiological human | |
| The concept of a virtual physical human is a sophisticated computer modelling tool, which compares observations of an individual patient and relates them to a vast dataset of observations of others with similar symptoms and known conditions. By processing all this information, the model can simulate the likely reaction of the individual patient to possible treatments or interventions. Such tools will not only improve the quality of treatment offered to patients who are already ill or injured, but could also be used in preventive medicine, to predict occurrence or worsening of specific diseases in people at risk, for example through family history. | 
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| Date Added: 18-05-2010 | Visits: 2981 | 
		