A Primary Study on Application of Artificial Neural Network in Classification of Pediatric Fracture Healing Time of the Lower Limb
@inproceedings{Malek2016APS, title={A Primary Study on Application of Artificial Neural Network in Classification of Pediatric Fracture Healing Time of the Lower Limb}, author={Sorayya Malek and Roshan Gunalan and S. Y. Kedija and C. F. Lau and Mogeeb A. A. Mosleh and Pozi Milow and H. Amber and Aik Saw}, booktitle={Practical Applications of Computational Biology \& Bioinformatics}, year={2016} }
In this study we examined the lower limb fracture in children and classified the healing time using supervised and unsupervised artificial neural network (ANN). Radiographs of long bones from 2009 to 2011 of lower limb fractures involving the femur, tibia and fibula from children ages 0 to 13 years, with ages recorded from the date and time of initial injury was obtained from the pediatric orthopedic unit in University Malaya Medical Centre. ANNs was developed using the following input: type of…
4 Citations
Random forest and Self Organizing Maps application for analysis of pediatric fracture healing time of the lower limb
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MACHINE LEARNING TECHNIQUE IN APPLICATION AND COMPARISON IN PEDIATRIC FRACTURE HEALING TIME KEDIJA FACULTY OF SCIENCE UNIVERSITY OF MALAYA
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It is concluded that RF, Decision Tree, SVM, ANN and SOM techniques can be used to assist in analysis of the healing time efficiently and contact area percentage of fracture, type of fractures, number of fractured bone and age as important variables in explaining the fracture healing pattern.
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