| Neural net applied to anthropological material: a methodical study on the human nasal skeleton. | |
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MedLine Citation:
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PMID: 16130825 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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A new information processing method, an artificial neural net, was applied to characterise the variability of anthropological features of the human nasal skeleton. The aim was to find different types of nasal skeletons. A neural net with 15*15 nodes was trained by 17 standard anthropological parameters taken from 184 skulls of the Aachen collection. The trained neural net delivers its classification in a two-dimensional map. Different types of noses were locally separated within the map. Rare and frequent types may be distinguished after one passage of the complete collection through the net. Statistical descriptive analysis, hierarchical cluster analysis, and discriminant analysis were applied to the same data set. These parallel applications allowed comparison of the new approach to the more traditional ones. In general the classification by the neural net is in correspondence with cluster analysis and discriminant analysis. However, it goes beyond these classifications because of the possibility of differentiating the types in multi-dimensional dependencies. Furthermore, places in the map are kept blank for intermediate forms, which may be theoretically expected, but were not included in the training set. In conclusion, the application of a neural network is a suitable method for investigating large collections of biological material. The gained classification may be helpful in anatomy and anthropology as well as in forensic medicine. It may be used to characterise the peculiarity of a whole set as well as to find particular cases within the set. |
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Authors:
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Andreas Prescher; Anne Meyers; Diedrich Gerf von Keyserlingk |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Annals of anatomy = Anatomischer Anzeiger : official organ of the Anatomische Gesellschaft Volume: 187 ISSN: 0940-9602 ISO Abbreviation: Ann. Anat. Publication Date: 2005 Jul |
Date Detail:
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Created Date: 2005-08-31 Completed Date: 2005-10-05 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 100963897 Medline TA: Ann Anat Country: Germany |
Other Details:
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Languages: eng Pagination: 261-9 Citation Subset: IM |
Affiliation:
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Institut für Anatomie der RWTH Aachen, Wendlingweg 2, Aachen D-52074, Germany. aprescher@ukaachen.de |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Adult Aged Aged, 80 and over Aging Anthropology, Physical / methods Bone Development Cadaver Europe European Continental Ancestry Group Female Humans Male Middle Aged Nasal Bone / anatomy & histology* Neural Networks (Computer) Skull / anatomy & histology* |
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