Utilize este identificador para referenciar este registo: https://hdl.handle.net/10316/44333
Título: AncesTrees: ancestry estimation with randomized decision trees
Autor: Navega, David 
Coelho, Catarina 
Vicente, Ricardo 
Ferreira, Maria Teresa 
Wasterlain, Sofia 
Cunha, Eugénia 
Palavras-chave: Adult; Algorithms; Ethnic Groups; Female; Forensic Anthropology; Humans; Machine Learning; Male; Sex Determination by Skeleton; Cephalometry; Continental Population Groups; Databases as Topic; Decision Trees
Data: 2014
Projeto: info:eu-repo/grantAgreement/FCT/5876/147309/PT 
Título da revista, periódico, livro ou evento: International Journal of Legal Medicine
Volume: 129
Número: 5
Resumo: In forensic anthropology, ancestry estimation is essential in establishing the individual biological profile. The aim of this study is to present a new program--AncesTrees--developed for assessing ancestry based on metric analysis. AncesTrees relies on a machine learning ensemble algorithm, random forest, to classify the human skull. In the ensemble learning paradigm, several models are generated and co-jointly used to arrive at the final decision. The random forest algorithm creates ensembles of decision trees classifiers, a non-linear and non-parametric classification technique. The database used in AncesTrees is composed by 23 craniometric variables from 1,734 individuals, representative of six major ancestral groups and selected from the Howells' craniometric series. The program was tested in 128 adult crania from the following collections: the African slaves' skeletal collection of Valle da Gafaria; the Medical School Skull Collection and the Identified Skeletal Collection of 21st Century, both curated at the University of Coimbra. The first step of the test analysis was to perform ancestry estimation including all the ancestral groups of the database. The second stage of our test analysis was to conduct ancestry estimation including only the European and the African ancestral groups. In the first test analysis, 75% of the individuals of African ancestry and 79.2% of the individuals of European ancestry were correctly identified. The model involving only African and European ancestral groups had a better performance: 93.8% of all individuals were correctly classified. The obtained results show that AncesTrees can be a valuable tool in forensic anthropology.
URI: https://hdl.handle.net/10316/44333
DOI: 10.1007/s00414-014-1050-9
Direitos: embargoedAccess
Aparece nas coleções:I&D CIAS - Artigos em Revistas Internacionais

Ficheiros deste registo:
Ficheiro Descrição TamanhoFormato
cias2015_37.pdf692.53 kBAdobe PDFVer/Abrir
Mostrar registo em formato completo

Citações SCOPUSTM   

77
Visto em 25/mar/2024

Citações WEB OF SCIENCETM
5

58
Visto em 2/mar/2024

Visualizações de página 50

532
Visto em 26/mar/2024

Downloads

653
Visto em 26/mar/2024

Google ScholarTM

Verificar

Altmetric

Altmetric


Este registo está protegido por Licença Creative Commons Creative Commons