minedICE: A Knowledge Discovery Platform for Neurophysiological Artificial Intelligence

  • Rory A. Lewis
  • Allen Waziri
Conference paper

DOI: 10.1007/978-3-642-21916-0_61

Volume 6804 of the book series Lecture Notes in Computer Science (LNCS)
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

Abstract

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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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Rory A. Lewis
    • 1
    • 2
  • Allen Waziri
    • 3
  1. 1.Department of Computer ScienceUniversity of Colorado at Colorado SpringsColorado SpringsUSA
  2. 2.Departments of Pediatrics & NeurologyUniversity of Colorado DenverDenverUSA
  3. 3.Department of NeurosurgeryUniversity of Colorado DenverDenverUSA