A knowledge-driven agent-centred framework for data mining in EMG.
In this paper, we present a multi-agent framework for data mining in electromyography. This application, based on a web interface, provides a set of functionalities allowing to manipulate 1000 medical cases and more than 25,000 neurological tests stored in a medical database. The aim is to extract medical information using data mining algorithms and to supply a knowledge base with pertinent information. The multi-agent platform gives the possibility to distribute the data management process between several autonomous entities. This framework provides a parallel and flexible data manipulation.
Balter
Julien
J
Laboratoire TIMC-IMAG, institut Bonniot, faculté de médecine, domaine de la Merci, 38706 La Tronche, France.
Labarre-Vila
Annick
A
Ziébelin
Danielle
D
Garbay
Catherine
C
D003625:Data Collection / Q000379:methods*; D003627:Data Interpretation, Statistical; D003628:Database Management Systems; D016208:Databases, Factual; D004576:Electromyography / Q000379:methods*; D006801:Humans; D009460:Neurologic Examination