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Ensembling rules in automatic analysis of pressure on plantar surface in children with pes planovalgus.
Advances in Medical Sciences 2019 Februrary 2
PURPOSE: This paper presents a method of ensembling rules obtained through induction of several basic types of decision trees.
MATERIAL AND METHODS: The proposed method uses rules generated by means of well-known decision trees: CART, CHAID, exhaustive CHAID and C4.5. The method was tested on data describing pressure distribution under foot during gait in children with pes planovalgus (PV) and typical foot. Children with pes planovalgus underwent surgical intervention and were re-examined. Overall, 316 gait cycles have been used in analysis.
RESULTS: The obtained results consist of a set of rules for all considered cases and show that the proposed method may be a useful tool of gait analysis on the basis of parameters that have a physical interpretation.
CONCLUSIONS: The presented method for mining rules useful in this respect may be successfully used by persons with a typically medical knowledge and could improve the understanding of the human gait phenomenon. There is obviously no reason why this method could not be used in the case of other data as well.
MATERIAL AND METHODS: The proposed method uses rules generated by means of well-known decision trees: CART, CHAID, exhaustive CHAID and C4.5. The method was tested on data describing pressure distribution under foot during gait in children with pes planovalgus (PV) and typical foot. Children with pes planovalgus underwent surgical intervention and were re-examined. Overall, 316 gait cycles have been used in analysis.
RESULTS: The obtained results consist of a set of rules for all considered cases and show that the proposed method may be a useful tool of gait analysis on the basis of parameters that have a physical interpretation.
CONCLUSIONS: The presented method for mining rules useful in this respect may be successfully used by persons with a typically medical knowledge and could improve the understanding of the human gait phenomenon. There is obviously no reason why this method could not be used in the case of other data as well.
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