Abstract
Recently, we have experienced a growth and a technological revolution in all areas such as industry, e-commerce, economics and health. To get more out of this digital revolution, we based our studies on statistics and in-depth research that we have carried out in the field of health in general and mental health in particular. In this context we have thought of improving the automation and personalization of the process of analysing electronic medical records in order to develop a decision support tool, for the benefit of psychologists and psychiatrists, so that we can predict in advance the most confronted psychological pathologies. To this end, we used the formalism of the languages previously proposed in this context, namely Machine Learning, Big data, the GATE development platform for Automatic Processing of Medical Language as well as the Medical Language Unification System “UMLS” for mapping and classification of pathologies and data from electronic medical records. To achieve these ends, we have developed the web platform “Medico-call”, which provides a service of psychological support and support. We then plan to add an additional boost by making a comparison between the prediction results psychological pathologies from consultations and clinical data as well as web data from our platform, this in the context of strengthening the performance as well as the quality of the tools and technologies described above.
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Taoussi, C., Hafidi, I., Metrane, A., Lasbahani, A. (2021). Predicting Psychological Pathologies from Electronic Medical Records. In: Ahram, T., Taiar, R., Groff, F. (eds) Human Interaction, Emerging Technologies and Future Applications IV. IHIET-AI 2021. Advances in Intelligent Systems and Computing, vol 1378. Springer, Cham. https://doi.org/10.1007/978-3-030-74009-2_63
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DOI: https://doi.org/10.1007/978-3-030-74009-2_63
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