Agents vote against Falls: The Agent Perspective in EPRs
Abstract
Awarded with the PAAMS'13 IBM Award of Scientific Excellence for its Scientific Quality.
In this work we present an agent-based fall-risk assessment tool which is self-learning. As part of a mobile electronic patient record (EPR) each patient is represented by its agent which helps to lift the treasure of data offered by combining multiple EPRs in order to reveal personalized health-care. To learn from the data provided by the population under care, we enabled the patient agents to negotiate about possible fall-risk indicators using a distributed information fusion and opinion aggregation technique.
Autoren:
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Tagungsbeitrag
Jahr:
2013
Ort:
11th International Conference on Practical Applications of Agents and Multi-Agent Systems (Awarded with the IBM Award of Scientific Excellence)