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Sex Determination in Forensic Dentistry Using Supervised Classification Techniques
Ram\ń Álvarez-Vaz, Carlos Sassi

Sex Determination in Forensic Dentistry Using Supervised Classification Techniques

Author / Organization:
Science & Mathematics Published 2020 Verification Pending

Overview & Synopsis

Teeth, essential components of stomatognatrhic system, constitute an excellent material for paleontological, archaeological, anthropological, genetic and forensic researches by virtue of their easy accessibility, examination, registration and almost indestructible structure. Information regarding their size and characteristics has been extremely useful in determining sex and in the process of human identification itself. This survey was an odontometric analysis of 481 upper dental stone casts (243 from males and 238 from females), of patients aged between 18 and 60 years, assisted in one orthodontic clinic of Montevideo, Uruguay, consisting of measurements of upper mesiodistal diameter of canines and intercanine distance.Three sex classification techniques were compared, the maxillary canine index and two supervised classification methods (classification tree and recursive partitioned tree), seeking to verify which method was the most suitable for the determination of sex, in a Uruguayan sample. The models showed a performance of 52 %, 77 % and 69 % respectively. It was concluded that the statistical models of supervised classification allowed a determination of the sex in a more reliable way than the discrimination method.

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Document Information

Document Title Sex Determination in Forensic Dentistry Using Supervised Classification Techniques
Author / Organization Ram\ń Álvarez-Vaz, Carlos Sassi
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2020
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-241217
Original Source Link Visit Source Page on hal.science »