Metric Rule Generation with Septic Shock Patient Data
نویسنده
چکیده
In this contribution we present an application of metric rule generation in the domain of medical research. We consider intensive care unit patients developing a septic shock during their stay at the hospital. To analyse the patient data, rule generation is embedded in a medical data mining cycle. For rule generation, we improve an architecture based on a growing trapezoidal basis function network.
منابع مشابه
Rule generation and model selection used for medical diagnosis
In medical data analysis classification combined with rule generation is a common technique to obtain diagnosis results together with a rule based explanation. In this contribution we apply a neural network based rule generator in the domain of septic shock research. The septic shock is of special interest in intensive care medicine due to its high lethality rate. We describe the functionality ...
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تاریخ انتشار 2001