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    The effect of altitude and climate on the suicide rates in Turkey
    (Elsevier Sci Ltd, 2018) Asirdizer, Mahmut; Kartal, Erhan; Etli, Yasin; Tatlisumak, Ertugrul; Gumus, Orhan; Hekimoglu, Yavuz; Keskin, Siddik
    Suicide is one of the most important public health problems. There was an association between suicide and several factors such as psychiatric diseases and psychological characteristics, somatic illness, cultural, socioeconomic, familial, occupational and individual risk factors. Also, high altitude and climatic factors including high temperature, cloudiness, more sunshine and low rainfalls were defined as some of these risk factors in the literature. In this study, we aimed to investigate correlation between suicide rates and altitudes of all cities in Turkey and between suicide rates and climatic factors including Rainfall Activity Index, Winter Mean Temperatures, Summer Mean Temperatures and Temperature Difference between January and July previously defined by several authors in the broad series in Turkey. In Turkey, 29865 suicidal deaths occurred in 10 years period between 2006 and 2015. Of them, 21020 (70.4%) were males and 8845 (29.6%) were females. In this study, we found that high altitude above 1500 m, winter median temperature lower than - 10 degrees C and hard temperature changes above 25 degrees C between winter and summer of settlements were important factors that affected on female suicide rates appropriate to knowledge which defined in previous studies. In conclusion, we suggested that the associations among suicide rates with altitudes and climate should be studied in wider series obtained from different countries for reaching more reliable results.
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    Sex estimation using foramen magnum measurements, discriminant analyses and artificial neural networks on an eastern Turkish population sample
    (Elsevier Ireland Ltd, 2022) Kartal, Erhan; Etli, Yasin; Asirdizer, Mahmut; Hekimoglu, Yavuz; Keskin, Siddik; Demir, Ugur; Yavuz, Alparslan
    Background: Although many studies have been conducted using the foramen magnum for sex estimation, recent findings have indicated that the discriminant and regression models obtained from the foramen magnum may not be reliable. Artificial Neural Networks, was used as a classification technique in sex estimation studies on some other bones, did not used in sex estimation studies on the foramen magnum until now. The aim of this study was sex estimation on an Eastern Turkish population sample using foramen magnum measurements, discriminant analyses and Artificial Neural Networks. Methodology: The study was performed on the CT images of a total of 720 cases, comprising 360 males and 360 females. For sex estimation, discriminant analysis and Artificial Neural Networks were used. Results: The accuracy rate was 86.7% with discriminant analysis and when sex estimation accuracy was deter-mined according to cases with posterior probabilities above 95%, the accuracy ranged from 0% to 33.3%. With the use of the discriminant formulas of 2 other studies, obtained from different Turkish samples, sex could be determined at a rate of 84.6%. Some formulas were found to be unsuccessful in sex estimation. Sex estimation accuracy of 88.2% was achieved with Artificial Neural Networks.Conclusion: In this study, it was found that sex could be determined to some extent with discriminant formulas from other samples from the same population, although some formulas were unsuccessful. With the use of image processing techniques and machine learning algorithms, better results can be obtained in sex estimation.