Title :
Metric rule generation with septic shock patient data
Author_Institution :
Inst. fur Informatik, J.W. Goethe-Universitat, Frankfurt am Main, Germany
Abstract :
The article 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
Keywords :
data mining; learning (artificial intelligence); medical expert systems; medical information systems; growing trapezoidal basis function network; hospital; intensive care unit patients; medical data mining cycle; medical research; metric rule generation; patient data analysis; septic shock patient data; Abdomen; Data analysis; Data mining; Data preprocessing; Databases; Electric shock; Fuzzy neural networks; Hospitals; Immune system; Neurons;
Conference_Titel :
Data Mining, 2001. ICDM 2001, Proceedings IEEE International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
0-7695-1119-8
DOI :
10.1109/ICDM.2001.989587
