Comparison of mandibular morphometric parameters in digital panoramic radiography in gender determination using machine learning
Küçük Resim Yok
Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
ObjectiveThis study aimed to evaluate the usability of morphometric features obtained from mandibular panoramic radiographs in gender determination using machine learning algorithms.Materials and methodsHigh-resolution radiographs of 200 patients aged 20-77 (41.0 +/- 12.7) were included in the study. Twelve different morphometric measurements were extracted from each digital panoramic radiography included in the study. These measurements were used as features in the machine learning phase in which six different machine learning algorithms were used (k-nearest neighbor, decision trees, support vector machines, naive Bayes, linear discrimination analysis, and neural networks). To evaluate the reliability, we have performed tenfold cross-validation and we repeated this 10 times for every classification process. This process enhances the reliability of the results for other datasets.ResultsWhen all 12 features are used together, the accuracy rate is found to be 82.6 +/- 0.5%. The classification accuracies are also compared using each feature alone. Three features that give the highest accuracy are coronoid height (80.9 +/- 0.9%), condyle height (78.2 +/- 0.5%), and ramus height (77.2 +/- 0.4%), respectively. When compared to the classification algorithms, the highest accuracy was obtained with the naive Bayes algorithm with a rate of 84.0 +/- 0.4%.ConclusionMachine learning techniques can accurately determine gender by analyzing mandibular morphometric structures from digital panoramic radiographs. The most precise results are achieved by evaluating the structures in combination, using attributes obtained from applying the MRMR algorithm to all features.
Açıklama
Anahtar Kelimeler
Machine learning, Forensic science, & Idot;mage processing, Digital panoramic radiography, Gender determination, Mandibular morphometric parameters
Kaynak
Oral Radiology
WoS Q Değeri
N/A
Scopus Q Değeri
Q2
Cilt
40
Sayı
3
