Machine Learning Preprocessing Method for Suicide Prediction
The main objective of this study was to find a preprocessing method to enhance the effectiveness of the machine learning methods in datasets of mental patients. Specifically, the machine learning methods must have almost excellent classification results i
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Medical Informatics Lab, Medical School, Democritus University of Thrace, Komotini, Greece [email protected] 2 Special Office for Health Consulting Services, University of Patras, Patras, Greece 3 Wire Communications Lab, Department of Electrical Engineer, University of Patras, Patras, Greece 4 Department of Psychiatry, University of Patras, Patras, Greece
Abstract. The main objective of this study was to find a preprocessing method to enhance the effectiveness of the machine learning methods in datasets of mental patients. Specifically, the machine learning methods must have almost excellent classification results in patients with depression who have thoughts of suicide, in order to achieve the sooner the possible the appropriate treatment. In this paper, we establish a novel data preprocessing method for improving the prognosis’ possibilities of a patient suffering from depression to be leaded to the suicide. For this reason, the effectiveness of many machine learning classification algorithms is measured, with and without the use of our suggested preprocessing method. The experimental results reveal that our novel proposed data preprocessing method markedly improved the overall performance on initial dataset comparing with PCA and Evolutionary search feature selection methods. So this preprocessing method can be used for significantly boost classification algorithms performance in similar datasets and can be used for suicide tendency prediction. Keywords: Data preprocessing Classification Feature selection illness
Principal component analysis Suicidal ideation Depression Mental
1 Introduction Suicidal ideation is generally associated with depression and other mood disorders. However, it seems to have associations with many other psychiatric disorders, life events, and family events, all of which may increase the risk of suicidal ideation. For example, many people with borderline personality disorder exhibit recurrent suicidal behavior and suicidal ideation. One study found that 73 % of patients with borderline personality disorder have attempted suicide, with the average patient having 3 or 4 attempts. © IFIP International Federation for Information Processing 2016 Published by Springer International Publishing Switzerland 2016. All Rights Reserved L. Iliadis and I. Maglogiannis (Eds.): AIAI 2016, IFIP AICT 475, pp. 53–60, 2016. DOI: 10.1007/978-3-319-44944-9_5
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Early detection and treatment are the best ways to prevent suicidal ideation and suicide attempts. If signs, symptoms, or risk factors are detected early then the person will hopefully seek for treatment and help before attempting to take his/her own life. In a study of people who did commit suicide, 91 % of them likely suffered from one or more mental illnesses. Nevertheless, only 35 % of those people were treated or being treated for a mental illness. This emphasizes the importance of early detection; if a mental illness is detected, it can be treated and controlled to help prevent suicide attempts. Another study investig
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