Hybrid Expert System Advisor for Anaestetic Control and Intense Care Using Adaptive Neuro Fuzzy Inference System and Certainty Factors

  • Abstract
  • Keywords
  • References
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  • Abstract

    Despite the great advances in medicine and technology, there are some risks to the life of the patient suffering from anesthesia and intensive care, and the reason that the human has a restricted capability to continuously and accurately analyse huge amount of patients data. Most methods previously used do not give accurate results because they use a single pointer. Therefore, in this research, many artificial intelligence techniques and quantitative measurements have been merge into an a to support doctors decision in controlling anesthesia and intensive care. This research was designed as an intelligent hybrid system as an anesthesia consultant by incorporating of rule-based, adaptive neuro-fuzzy inference system, fuzzy control and certainty factor theory that can simulate an anesthesiologist in thinking and making appropriate decisions in complex circumstances. The aim of this research is to improve clinical diagnosis and detect critical events during anesthesia by relying on artificial intelligence methods.



  • Keywords

    Expert system, anaesthesia, fuzzy control, ANFIS, certainty factor.

  • References

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Article ID: 27007
DOI: 10.14419/ijet.v7i4.25.27007

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