Analysis of data concerning risk of suicide in mentally ill patients

Hron, Jiří

The three goals of this thesis are to present a coherent overview of the research on suicide in both the general population and among mentally ill, to analyse records of hospitalisations of mentally ill from years 2006 to 2012 while looking for patterns either leading to identification of suicide risk factors or useful for predicting probability of suicide at the time of discharge, and finally to compare a selected subset of statistical, data mining and machine learning methods in relation to their applicability to the second goal. The overview is based on information from over 40 published articles. The analysis and the comparison make use of associative rules mining, visual and stepwise methods for exploration, standard and conditional logistic regression models for inference, and variations of random forests for prediction. To the best of author's knowledge, none of the three goals was previously pursued by any other researcher in the Czech Republic, certainly not using the data set provided for purposes of this thesis. A new modification of random forest combined with a set of logistic regression in order to refine prediction accuracy is also briefly explored. The structure closely follows the above--stated goals starting from the chapters on related work and on the theoretical basis of the methods used, and concluding by the analysis itself and discussion of its results.

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