minedICE: A Knowledge Discovery Platform for Neurophysiological Artificial Intelligence
- Cite this paper as:
- Lewis R.A., Waziri A. (2011) minedICE: A Knowledge Discovery Platform for Neurophysiological Artificial Intelligence. In: Kryszkiewicz M., Rybinski H., Skowron A., Raś Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2011. Lecture Notes in Computer Science, vol 6804. Springer, Berlin, Heidelberg
In this paper we present the minedICETM computer architecture and network comprised of neurological instruments and artificial intelligence (AI) agents. It’s called minedICE because data that is “mined” via IntraCortical Electroencephalography (ICE) located deep inside the human brain procures (mined) knowledge to a Decision Support System (DSS) that is read by a neurosurgeon located either at the bedside of the patient or at a geospatially remote location. The DSS system 1) alerts the neurosurgeon when a severe neurological event is occurring in the patient and 2) identifies the severe neurological event. The neurosurgeon may choose to provide feedback to the AI agent which controls the confidence level of the association rules and thereby teaches the learning component of minedICE.
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