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Автор: Roux E., Thiessard F., Fourrier A., Begaud B., TubertBitter P.
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Ключові слова:
комп'ютерне моделювання, компьютерное моделирование, computer modeling ; інформаційні системи, информационные системы, information systems, systemes d'information
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Анотація:
Pharmacovigilance aims at detecting the adverse effects of marketed drugs. It is generally based on the spontaneous reporting of events thought to be the adverse effects of drugs. Spontaneous Reporting Systems (SRSs) supply huge databases that pharmacovigilance experts cannot exhaustively exploit without data mining tools. Data mining methods; i.e., statistical associationmeasures in conjunction with signal generation criteria, have been proposed in the literature but there is no consensus regarding their applicability and efficiency, especially since such methods are difficult to evaluate on the basis of actual data. The objective of this paper is to evaluate association measures on simulated datasets obtained with SRS modeling. We compared association measures using the percentage of false positive signals among a given number of the most highly ranked drug–event combinations according to the values of the associationmeasures. By сonsidering 150 drugs and 100 adverse events, these percentages of f
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