Editorial: Hybrid learning machines
Neurocomputing
A First Study on the Use of Coevolutionary Algorithms for Instance and Feature Selection
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Editorial: Hybrid intelligent algorithms and applications
Information Sciences: an International Journal
Designing fusers on the basis of discriminants – evolutionary and neural methods of training
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
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The history of patient classification in nursing dates back to the period of Florence Nightingale. The first and the foremost condition for providing quality nursing care, which is measured by care standards, and determined by number of hours of actual care, is the appropriate number of nurses. Patient classification criteria are discussed in this paper. Hybrid classification model based on learning vector quantization (LVQ) networks and self-organising maps (SOM) are purposed. It is possible to discus three types of experimental results. First result could be assessment of Braden scale and Mors scale by LVQ. Second result, the time for nursing logistics activities. The third is possibility to predict appropriate number of nurses for providing quality nursing care. This research was conducted on patients from Institute of Neurology, Clinical Centre of Vojvodina.