Pregled bibliografske jedinice broj: 1083414
Principal Component Regression for Forensic Age Determination Using the Raman Spectra of Teeth
Principal Component Regression for Forensic Age Determination Using the Raman Spectra of Teeth // Applied Spectroscopy, 74 (2020), 12; 1473-1485 doi:10.1177/0003702820905903 (međunarodna recenzija, članak, znanstveni)
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Naslov
Principal Component Regression for Forensic Age
Determination Using the Raman Spectra of Teeth
Autori
Osmani, Aziz ; Par, Matej ; Škrabić, Marko ; Vodanović, Marin ; Gamulin, Ozren
Izvornik
Applied Spectroscopy (0003-7028) 74
(2020), 12;
1473-1485
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
raman spectrometry ; principal component analysis ; PCA ; principal component regression ; PCR ; age determination ; forensic dentistry
Sažetak
Raman spectra of mineralized tooth tissues were used to build a principal component regression (PCR) age determination model for forensic application. A sample of 71 teeth was obtained from donors aging from 11 to 76 years. No particular selection criteria were applied ; teeth affected with various pathological processes were deliberately included to simulate a realistic forensic scenario. In order to comply with the nondestructive specimen handling, Raman spectra were collected from tooth surfaces without any previous preparation. Different tooth tissues were evaluated by collecting the spectra from three distinct sites: tooth crown, tooth neck, and root apex. Whole recorded spectra (3500–200 cm−1) were used for principal component analysis and building of the age determination model using PCR. The predictive capabilities of the obtained age determination models varied according to the spectra collection site. Optimal age determination was attained by using Raman spectra collected from cementum at root apex (R2 values of 0.84 and 0.71 for male and female donors, respectively). For optimal performance of that model, male and female donors had to be analyzed separately, as merging both genders into a single model considerably diminished its predictive capability (R2 = 0.29).
Izvorni jezik
Engleski
Znanstvena područja
Fizika, Dentalna medicina
POVEZANOST RADA
Ustanove:
Stomatološki fakultet, Zagreb,
Medicinski fakultet, Zagreb
Citiraj ovu publikaciju:
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