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    The importance of forensic medicine education: A questionnaire survey
    (2024) Altın, Ismail; Parlak, Muhammed Emin; Gorugel, Ayfer; Oruc, Mucahit; Celbıs, Osman; Yılmaz, Mesut
    Aim: Forensic medicine is one of the basic areas of duty and responsibility of physicians just like the preventative, diagnostic, and treatment services of medicine. The aim of this study was to emphasise the importance of practice-based theoretical forensic medicine education by evaluating students who had taken and not taken forensic medicine internship. Materials and Methods: Two groups were formed of students who had taken and not taken practice-based forensic medicine internship. A questionnaire of 24 items was administered to the students to evaluate their level of knowledge related to forensic medicine and expertise. The data obtained were analyzed statistically using SPSS vn. 24 software (IBM SPSS, Somers, NY, USA). Results: There were seen to be statistically significant differences between the groups in the responses to many of the questions. Students who had not taken a forensic medicine internship felt that their knowledge was lacking on subjects related to forensic medicine, and the results showed deficiencies in these subjects. Conclusion: Consistent with findings in literature, students who had not taken a forensic medicine internship felt inadequate in areas related to forensic medicine services and it was seen that their knowledge related to these subjects was lacking. Forensic medicine education should be an integral part of the medical faculty syllabus.
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    Sex and stature estimation from anthropometric measurements of the foot: linear analyses and neural network approach on a Turkish sample
    (Int Assoc Law & Forensic Sciences, 2024) Parlak, Muhammed Emin; Oezkul, Bengue Berrak; Oruc, Mucahit; Celbis, Osman
    Background For over a century, anthropometric techniques, widely used by anthropologists and adopted by medical scientists, have been utilized for predicting stature and sex. This study, conducted on a Eastern Turkish sample, aims to predict sex and stature using foot measurements through linear methods and Artificial Neural Networks. Our research was conducted on 134 medical students, comprising 69 males and 65 females. Stature and weight were measured in a standard anatomical position in the Frankfurt Horizontal Plane with a stadiometer of 0.1 cm precision. Measurements of both feet's height, length, and breadth were taken using a Vernier caliper, osteometric board, and height scale. The data were analyzed using SPSS 26.00.Results It was observed that all foot dimensions in males were significantly larger than in females. Sex prediction using linear methods yielded an accuracy of 94.8%, with a stature estimation error of 4.15 cm. When employing Artificial Neural Networks, sex prediction accuracy increased to 97.8%, and the error in stature estimation was reduced to 4.07 cm.Conclusions Our findings indicate that Artificial Neural Networks can work more effectively with such data. Using Artificial Neural Networks, the accuracy of sex prediction for both feet exceeded 95%. Additionally, the error in stature estimation was reduced compared to the formulas obtained through linear methods.