Sekazu: an integrated solution tool for gender determination based on machine learning models
Yazarlar (4)
Doç. Dr. Muhammed Kamil TURAN Karabük Üniversitesi, Türkiye
Doç. Dr. Eftal ŞEHİRLİ Karabük Üniversitesi, Türkiye
Prof. Dr. Zülal Öner Karabük Üniversitesi, Türkiye
Serkan Öner Karabük Üniversitesi, Türkiye
Makale Türü Açık Erişim Özgün Makale (Ulusal alan endekslerinde (TR Dizin, ULAKBİM) yayınlanan tam makale)
Dergi Adı Medicine Science | International Medical Journal
Dergi ISSN 2147-0634
Dergi Tarandığı Indeksler TR DİZİN
Makale Dili İngilizce Basım Tarihi 03-2021
Kabul Tarihi Yayınlanma Tarihi 01-01-2021
Cilt / Sayı / Sayfa 10 / 2 / 363–373 DOI 10.5455/medscience.2020.11.248
Makale Linki http://dx.doi.org/10.5455/medscience.2020.11.248
UAK Araştırma Alanları
Makine Öğrenmesi
Özet
Gender determination is the first stage of identification used in forensic investigation, anthropology, archeology, and bioarchaeology, which helps accelerate the process of narrowing possible matches in a medical-legal context. Without DNA analysis, the dimorphic property of bones comprises a basis for gender determination with measurements taken on only bones. In this work, 9 different bones such as cranium, mandibula, femur, patella, calcaneus, condylus occipitalis, sternum, hand bones, and foot bones were used for gender determination. Machine learning methods and artificial neural networks, especially linear and quadratic discriminant analysis, while determining the gender, machine learning also were technically adopted. 13 different machine learning algorithms were used as a model for gender determination. Many tools were designed to perform processes like designing necessary bookmarks to try models, designing measurements where machine learning algorithms are used as features, determining coordinates of designed bookmarks, and computation of features. A software named Sekazu was developed by presenting an integrated solution proposal. Thanks to the developed software, models used in gender determination were developed and tried in a fast way and researchers can obtain results reported based on performance metrics flexibly.
Anahtar Kelimeler
BM Sürdürülebilir Kalkınma Amaçları
Atıf Sayıları
Google Scholar 7
Sekazu: an integrated solution tool for gender determination based on machine learning models

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