Dergiler / European Journal of Technique / 2017 / Cilt: 7 - Sayı: 2

COMPARISON OF THE CLASSIFICATION PERFORMANCES OF CRIMINAL TENDENCIES OF SCHIZOPHRENIC PATIENTS BY ARTIFICIAL NEURAL NETWORKS AND SUPPORT VECTOR MACHINE

Sayfa
177–185
Yayın Tarihi
2017-12-30
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

According to classification results, it was seen that the biochemical data used could be useful features in the determination of the criminal tendencies of schizophrenic patients.

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Amaç & Hipotez:In this study, a new approach based on Artificial Neural Networks (ANN) and Support Vector Machine (SVM) classifiers has been proposed in the determination of criminal tendency with biochemical data of schizophrenia patients.
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Temel Bulgular & Veri:The data were obtained from 100 schizophrenic inpatients in Elazığ mental and Neurological Disorders Hospital.
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Sonuç & Katkı:According to classification results, it was seen that the biochemical data used could be useful features in the determination of the criminal tendencies of schizophrenic patients.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Schizophrenia · Artificial neural network · Support vector machine

Abstract

In this study, a new approach based on Artificial Neural Networks (ANN) and Support Vector Machine (SVM) classifiers has been proposed in the determination of criminal tendency with biochemical data of schizophrenia patients. Classification was performed using the biochemical data of the offender and control group schizophrenic patients. The data were obtained from 100 schizophrenic inpatients in Elazığ mental and Neurological Disorders Hospital. The biochemical data used for the examination and classification of the criminal tendencies of schizophrenic patients were Triglycerides, Total Cholesterol, High Density Lipoproteins (HDL), Low Density Lipoproteins (LDL), Very Low Density Lipoproteins (VLDL), Sex Hormone Binding Globulin (SHBG), Oestradiol, Free Testosterone, Total Testosterone, Ghrelin, Copper (Cu) and Zinc (Zn). Biochemical data were classified using ANN and SVM. All data were normalized to before classification. In addition, classifier results were evaluated using cross-validation method. As a result of the classification performed, 87% accuracy and 89% accuracy were achieved by ANN and SVM, respectively. In the determination of the criminal tendencies of schizophrenic patients using their biochemical data, SVM classifier performed a more effective classification compared to ANN classifier. According to classification results, it was seen that the biochemical data used could be useful features in the determination of the criminal tendencies of schizophrenic patients.

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Bu Makaleye Atıf Yap

DURSUN, Ö. O., TORAMAN, S., TÜRKOĞLU, A. (2017). COMPARISON OF THE CLASSIFICATION PERFORMANCES OF CRIMINAL TENDENCIES OF SCHIZOPHRENIC PATIENTS BY ARTIFICIAL NEURAL NETWORKS AND SUPPORT VECTOR MACHINE. European Journal of Technique, Cilt: 7 - Sayı: 2, 177–185. https://ajindex.com/articles/201951

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Kaynakça (11)

  1. A. Türkoğlu, “Suç İşlemiş ve İşlememiş Şizofrenik Hastalarda Bazı Biyokimyasal Parametrelerin Karşılaştırılması,” Fırat Üniversitesi,
  2. Tıp Fakültesi Adli Tıp Anabilim Dalı, Uzmanlık Tezi, Elazığ, 2008.
  3. E. Köroğlu and C. Güleç, Psikiyatri Temel Kitabı. Ankara: Hekimler Yayın Birliği, 1997. E. Belene, “Şizofreni’de Anksiyete Belirtilerinin, Pozitif, Negatif ve Depresif Belirtiler, İntihar Düşüncesi, İçgörü ve Yaşam Kalitesi Açısından İncelenmesi,” Sağlık Bakanlığı, Bakırköy Ord. Prof. Mazhar Osman Ruh Sağlığı ve Sinir Hastalıkları Eğitim Ve Araştırma Hastanesi, 2009. İ. Akdaş, “Şizofreni, Bipolar Affektif Bozukluk ve Anksiyete Tanısı Almış Hastalarda Toxoplasma Gondii Prevalansının Serolojik ve Moleküler Yöntemlerle Araştırılması,” Eskişehir Osmangazi Üniversitesi,
  4. Sağlık Bilimleri Enstitüsü, Yüksek Lisans Tezi, Eskişehir, 2013.
  5. A. Türkoğlu, M. Tokdemir, M. Atmaca, N. Mustafa, and B. Üstündağ, “Serum Cholesterol, Triglyceride, and Ghrelin Levels in Criminal and Non-criminal Schizophrenia Patients,” Bull. Clin. Psychopharmacol., vol. 19, no. 4, pp. 353–358, 2009.
  6. Ö. O. Dursun, S. Toraman, and A. Türkoğlu, “Determination Of The Crime Status Of Schizophrenia Patients With Sequential Backward Selection Algorithm,” in International Conference on Natural Science and Engineering (ICNASE’16), 2016, pp. 2347–2353.
  7. S. K. Bose, F. E. Turkheimer, O. D. Howes, M. A. Mehta, R. Cunliffe, P. R. Stokes, and P. M. Grasby, “Classification of schizophrenic patients and healthy controls using [18F] fluorodopa PET imaging,” Schizophr. Res., vol. 106, no. 2–3, pp. 148–155, 2008.
  8. R. C. W. Mandl, R. M. Brouwer, W. Cahn, R. S. Kahn, and H. E. Hulshoff Pol, “Family-wise automatic classification in schizophrenia,” Schizophr. Res., vol. 149, no. 1–3, pp. 108–111, 2013.
  9. M. Shim, H. J. Hwang, D. W. Kim, S. H. Lee, and C. H. Im, “Machine-learning-based diagnosis of schizophrenia using combined sensor-level and source-level EEG features,” Schizophr. Res., vol. 176, no. 2–3, pp. 314–319, 2016.
  10. L. Squarcina, C. Perlini, D. Peruzzo, U. Castellani, V. Marinelli, M. Bellani, G. Rambaldelli, A. Lasalvia, S. Tosato, K. De Santi, F. Spagnolli, R. Cerini, M. Ruggeri, P. Brambilla, and P.-V. Group, “The use of dynamic susceptibility contrast (DSC) MRI to automatically classify patients with first episode psychosis,” Schizophr. Res., vol. 165, no. 1, pp. 38–44, 2015.
  11. M. Takahashi, H. Hayashi, Y. Watanabe, K. Sawamura, N. Fukui, J. Watanabe, T. Kitajima, Y. Yamanouchi, N. Iwata, K. Mizukami, T. Hori, K.