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- W3004287972 abstract "Suicide is a worldwide public health problem. The World Health Organization (WHO) reports that suicide rates have increased by 60 % in the last forty years. Nowadays, suicide is the second cause of death in the 15-29 year old age bracket. Nonetheless, despite the visibility of the problem, reducing its incidence has proved challenging: there is no reliable method to predict suicide in any single individual. Rather, to curb this phenomenon, WHO recommends adopting populationwide prevention strategies centered around the timely diagnosis and treatment of mental illness. This poses a strain in local public health systems, which are commonly ill-equipped to screen large swats of the population for suicide-related disorders. Thus, recently, interest in finding computer-based solutions to optimize screening has surged. Among these, those based on textual pattern recognition are particularly promising: the extensive use of text communication online provides a rich source of information, where text-based screening methods may be able to flag patients at-risk that may have, otherwise, never been identified. In this work, some recent advances in the discipline are discussed." @default.
- W3004287972 created "2020-02-07" @default.
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- W3004287972 date "2019-10-01" @default.
- W3004287972 modified "2023-10-14" @default.
- W3004287972 title "Advances Towards the Identification of Mental Disorders Associated with Suicide through Text Processing" @default.
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- W3004287972 doi "https://doi.org/10.1109/contie49246.2019.00031" @default.
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