SPINNE: An app for human vertebral height estimation based on artificial neural networks
| Autor: | David Gonçalves, D. Vilas-Boas, Sofia N. Wasterlain, J. d’Oliveira Coelho, David Navega |
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| Jazyk: | portugalština |
| Rok vydání: | 2019 |
| Předmět: |
Adult
Male R language Adult male Biology 01 natural sciences Pathology and Forensic Medicine 03 medical and health sciences Young Adult 0302 clinical medicine Anatomical method medicine Humans 030216 legal & forensic medicine Adult female Artificial neural network 010401 analytical chemistry Forensic anthropology Anatomy Middle Aged Mobile Applications Body Height Spine 0104 chemical sciences medicine.anatomical_structure Vertebral height Forensic Anthropology Female Neural Networks Computer Law Vertebral column |
| Zdroj: | Repositório Científico de Acesso Aberto de Portugal Repositório Científico de Acesso Aberto de Portugal (RCAAP) instacron:RCAAP |
| Popis: | The absence or poor preservation of vertebrae often prevent the application of the anatomical method for stature estimation. The main objective of this paper was to develop a web app based on artificial neural network (ANN) models to estimate the vertebral height of absent or poorly preserved vertebrae from other vertebrae and thus enable the application of anatomical methods. Artificial neural models were developed based on the vertebral height of vertebrae C2 to S1 of a sample composed of 56 adult male and 69 adult female individuals. The skeletons belong to the Identified Skeletal Collection of the University of Coimbra and the ages at death of these individuals ranged from 22 to 58 years old. Statistical analysis and algorithmic development were performed with the R language, R Core Team (2018). Intra- and inter-observer errors regarding the vertebral height were small for all vertebrae ( |
| Databáze: | OpenAIRE |
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