부산대학교 도서관

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.