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Psikiyatride Makine Öğrenmesi Yöntemlerinin Kullanımı

Yıl 2021, Cilt: 13 Sayı: 2, 332 - 353, 30.06.2021
https://doi.org/10.18863/pgy.779987

Öz

Yapay zeka ve veri analizinde gün geçtikçe daha popüler hale gelen makine öğrenmesi yöntemleri birçok farklı alanda veriden öğrenmeyi sağlamaktadır. Sağlık alanında yapılan çalışmalarda bu yöntemler sağlık çalışanlarına ve hekimlere destek sunmaktadır. Psikiyatri de bu alanlardan bir tanesidir. Hastalıkların tanı, hastalık seyrinin tahmini veya bir tedaviye verilecek yanıtın gözlemlenmesi gibi problemlere makine öğrenmesi yöntemleri destek sağlamaktadır. Bu çalışma kapsamında psikiyatri alanında yapılmış olan makine öğrenmesi çalışmaları incelenmiştir. Çalışmanın amacı, makine öğrenmesi yöntemlerinin psikiyatri alanında kullanımının araştırılmasıdır. Özellikle elektroensefalografi (EEG) verisi kullanılan araştırmalara odaklanılmıştır. Bu amaçla, psikiyatride alanında yapılan makine öğrenmesi ile ilgili olan SCOPUS ve Google Scholar kaynaklarındaki yayınlar incelenmiştir. Literatürdeki genel durumun ortaya konması amacıyla, psikiyatri alanında makine öğrenmesi yöntemlerinden yararlanan çalışmalara incelenmiştir. Sonrasında ise daha detaylı bir şekilde psikiyatri alanında makine öğrenmesi ve EEG verisi kullanılarak yapılan araştırmalar incelenmiştir. Bu çalışmanın psikiyatride makine öğrenmesi ile ilgili yapılan yayınlar ve özellikle EEG verisi kullanılan yayınların derlenmesi açısından araştırmacılara faydalı olabileceği umulmaktadır.

Teşekkür

Bu çalışma İstanbul Üniversitesi Fen Bilimleri Enstitüsü Enformatik Anabilim Dalı’nda yürütülmekte olan doktora tez çalışmasından üretilmiştir.

Kaynakça

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Use of Machine Learning Methods in Psychiatry

Yıl 2021, Cilt: 13 Sayı: 2, 332 - 353, 30.06.2021
https://doi.org/10.18863/pgy.779987

Öz

Machine learning methods, which are becoming more and more popular in artificial intelligence and data analysis, provide learning from data in many different fields. In the studies conducted in the field of health, these methods support healthcare professionals and physicians. Psychiatry is one of these areas. Machine learning methods provide support to problems such as diagnosis, prediction of disease course or monitoring response to a treatment. In this study, machine learning studies in the field of psychiatry are examined.The aim of the study is to examine the studies of machine learning in the field of psychiatry and especially the studies conducted using electroencephalography (EEG) data. Accordingly, studies on machine learning in the field of psychiatry in SCOPUS and Google Scholar sources were examined. In order to reveal the general situation in the literature, studies using machine learning methods in the field of psychiatry were examined. Afterwards, studies using both machine learning methods and EEG data in psychiatry were examined. It is hoped that this study will be useful to researchers in terms of the publications about machine learning in psychiatry and especially the publications using EEG data.

Kaynakça

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  • Zhang X, Hu B, Zhou L, Moore P, Chen J. (2013) An EEG Based Pervasive Depression Detection for Females. Q. Zu, B. Hu ve A. Elçi (Ed.), Pervasive Computing and the Networked World içinde. Lecture Notes in Computer Science 7719:848-861. Joint International Conference on Pervasive Computing and the Networked World, Berlin, Heidelberg: Springer.
  • Zhao K ve So HC (2019) Drug Repositioning for Schizophrenia and Depression/Anxiety Disorders: A Machine Learning Approach Leveraging Expression Data. IEEE Journal of Biomedical and Health Informatics, 23(3):1304-1315. IEEE Journal of Biomedical and Health Informatics.
  • Zhao S, Zhao Q, Zhang X, Peng H, Yao Z, Shen J et al. (2017) Wearable EEG-Based Real-Time System for Depression Monitoring. Y. Zeng, Y. He, J. H. Kotaleski, M. Martone, B. Xu, H. Peng ve Q. Luo (Ed.), Brain Informatics içinde. Lecture Notes in Computer Science, 10654:190-201. Cham: Springer International Publishing.
  • Zilcha-Mano S, Roose SP, Brown PJ ve Rutherford BR. (2018) A Machine Learning Approach to Identifying Placebo Responders in Late-Life Depression Trials. The American journal of geriatric psychiatry: Official journal of the American Association for Geriatric Psychiatry, 26(6): 669-677.
Toplam 105 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Psikiyatri
Bölüm Derleme
Yazarlar

İlkim Ecem Emre 0000-0001-9507-8967

Cumhur Taş 0000-0002-4998-5272

Çiğdem Erol 0000-0002-5057-7145

Yayımlanma Tarihi 30 Haziran 2021
Kabul Tarihi 6 Kasım 2020
Yayımlandığı Sayı Yıl 2021 Cilt: 13 Sayı: 2

Kaynak Göster

AMA Emre İE, Taş C, Erol Ç. Psikiyatride Makine Öğrenmesi Yöntemlerinin Kullanımı. Psikiyatride Güncel Yaklaşımlar. Haziran 2021;13(2):332-353. doi:10.18863/pgy.779987

Creative Commons Lisansı
Psikiyatride Güncel Yaklaşımlar Creative Commons Atıf-Gayriticari-Türetilemez 4.0 Uluslararası Lisansı ile lisanslanmıştır.