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Pregled bibliografske jedinice broj: 1134461

Possibility of Human Gender Recognition Using Raman Spectra of Teeth


Gamulin, Ozren; Škrabić, Marko; Serec, Kristina; Par, Matej; Baković, Marija; Krajačić, Maria; Babić, Sanja Dolanski; Šegedin, Nikola; Osmani, Aziz; Vodanović, Marin
Possibility of Human Gender Recognition Using Raman Spectra of Teeth // Molecules, 26 (2021), 13; 3983, 17 doi:10.3390/molecules26133983 (međunarodna recenzija, članak, znanstveni)


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Naslov
Possibility of Human Gender Recognition Using Raman Spectra of Teeth

Autori
Gamulin, Ozren ; Škrabić, Marko ; Serec, Kristina ; Par, Matej ; Baković, Marija ; Krajačić, Maria ; Babić, Sanja Dolanski ; Šegedin, Nikola ; Osmani, Aziz ; Vodanović, Marin

Izvornik
Molecules (1420-3049) 26 (2021), 13; 3983, 17

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Raman spectroscopy ; multivariate statistical methods ; principal component analysis ; support vector machine ; artificial neural network ; forensic dentistry ; gender determination

Sažetak
Gender determination of the human remains can be very challenging, especially in the case of incomplete ones. Herein, we report a proof‐of‐concept experiment where the possibility of gender recognition using Raman spectroscopy of teeth is investigated. Raman spectra were recorded from male and female molars and premolars on two distinct sites, tooth apex and anatomical neck. Recorded spectra were sorted into suitable datasets and initially analyzed with principal component analysis, which showed a distinction between spectra of male and female teeth. Then, reduced datasets with scores of the first 20 principal components were formed and two classification algorithms, support vector machine and artificial neural networks, were applied to form classification models for gender recognition. The obtained results showed that gender recognition with Raman spectra of teeth is possible but strongly depends both on the tooth type and spectrum recording site. The difference in classification accuracy between different tooth types and recording sites are discussed in terms of the molecular structure difference caused by the influence of masticatory loading or gender‐dependent life events.

Izvorni jezik
Engleski

Znanstvena područja
Fizika, Dentalna medicina



POVEZANOST RADA


Projekti:
EK-EFRR-KK.01.1.1.01.0001 - Potpora vrhunskim istraživanjima Centra izvrsnosti za napredne materijale i senzore (Ivanda, Mile; Jakšić, Milko; Stipčević, Mario; Kralj, Marko, EK - KK.01.1.1.01) ( POIROT)

Ustanove:
Stomatološki fakultet, Zagreb,
Medicinski fakultet, Zagreb

Citiraj ovu publikaciju

Gamulin, Ozren; Škrabić, Marko; Serec, Kristina; Par, Matej; Baković, Marija; Krajačić, Maria; Babić, Sanja Dolanski; Šegedin, Nikola; Osmani, Aziz; Vodanović, Marin
Possibility of Human Gender Recognition Using Raman Spectra of Teeth // Molecules, 26 (2021), 13; 3983, 17 doi:10.3390/molecules26133983 (međunarodna recenzija, članak, znanstveni)
Gamulin, O., Škrabić, M., Serec, K., Par, M., Baković, M., Krajačić, M., Babić, S., Šegedin, N., Osmani, A. & Vodanović, M. (2021) Possibility of Human Gender Recognition Using Raman Spectra of Teeth. Molecules, 26 (13), 3983, 17 doi:10.3390/molecules26133983.
@article{article, year = {2021}, pages = {17}, DOI = {10.3390/molecules26133983}, chapter = {3983}, keywords = {Raman spectroscopy, multivariate statistical methods, principal component analysis, support vector machine, artificial neural network, forensic dentistry, gender determination}, journal = {Molecules}, doi = {10.3390/molecules26133983}, volume = {26}, number = {13}, issn = {1420-3049}, title = {Possibility of Human Gender Recognition Using Raman Spectra of Teeth}, keyword = {Raman spectroscopy, multivariate statistical methods, principal component analysis, support vector machine, artificial neural network, forensic dentistry, gender determination}, chapternumber = {3983} }
@article{article, year = {2021}, pages = {17}, DOI = {10.3390/molecules26133983}, chapter = {3983}, keywords = {Raman spectroscopy, multivariate statistical methods, principal component analysis, support vector machine, artificial neural network, forensic dentistry, gender determination}, journal = {Molecules}, doi = {10.3390/molecules26133983}, volume = {26}, number = {13}, issn = {1420-3049}, title = {Possibility of Human Gender Recognition Using Raman Spectra of Teeth}, keyword = {Raman spectroscopy, multivariate statistical methods, principal component analysis, support vector machine, artificial neural network, forensic dentistry, gender determination}, chapternumber = {3983} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


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