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The aim of this perspective is to provide a review upon the fundamental computational methods deployed in data mining as applied to healthcare data, with particular regards to patient records of psychiatric patients. Albeit clinical data mining has advanced over the years, further research is needed to improve the specificity of pharmacovigilance and prevent adverse drug reactions in psychiatric patients. From describing the main principles and present challenges of data mining to its most-novel applications in clinical psychiatry, this literature review highlights current research gaps that have to be filled to increase the efficacy of psychiatric drugs nowadays, thus improving patient outcomes and decreasing hospitalization costs.