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Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Decision Support Methods In Diabetic Patient Management By Insulin Administration Neural Network Vs. Induction Methods For Knowledge Classification, B. V. Ambrosiadou, S. Vadera, Venky Shankaraman, D. Goulis, G. Gogou
Decision Support Methods In Diabetic Patient Management By Insulin Administration Neural Network Vs. Induction Methods For Knowledge Classification, B. V. Ambrosiadou, S. Vadera, Venky Shankaraman, D. Goulis, G. Gogou
Research Collection School Of Computing and Information Systems
Diabetes mellitus is now recognised as a major worldwide public health problem. At present, about 100 million people are registered as diabetic patients. Many clinical, social and economic problems occur as a consequence of insulin-dependent diabetes. Treatment attempts to prevent or delay complications by applying ‘optimal’ glycaemic control. Therefore, there is a continuous need for effective monitoring of the patient. Given the popularity of decision tree learning algorithms as well as neural networks for knowledge classification which is further used for decision support, this paper examines their relative merits by applying one algorithm from each family on a medical problem; …
Fuzzy Neural Network Models For Classification, Arun D. Kulkarni, Charles D. Cavanaugh
Fuzzy Neural Network Models For Classification, Arun D. Kulkarni, Charles D. Cavanaugh
Arun Kulkarni
Neural Networks And Structured Knowledge: Rule Extraction And Applications, Franz J. Kurfess
Neural Networks And Structured Knowledge: Rule Extraction And Applications, Franz J. Kurfess
Computer Science and Software Engineering
As the second part of a special issue on "Neural Networks and Structured Knowledge," the contributions collected here concentrate on the extraction of knowledge, particularly in the form of rules, from neural networks, and on applications relying on the representation and processing of structured knowledge by neural networks. The transformation of the low-level internal representation in a neural network into higher-level knowledge or information that can be interpreted more easily by humans and integrated with symbol-oriented mechanisms is the subject of the first group of papers. The second group of papers uses specific applications as starting point, and describes approaches …