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Signal management in pharmacovigilance is a process of multiple activities evaluating risks associated with a particular medicinal product, or whether known risks associated with a particular drug have changed in frequency or severity. The signal management process follows a systematic approach: Signal detection, Signal Validation Signal prioritization, Signal assessment, Recommendation for action, and finally Exchange of information. Signal detection is the most vital part of signal management. Traditional methods include usage of solitary algorithms which are not accompanied by additional features of qualitative data mining resulting in mediocre performance. TCS scientists devised a hybrid approach in which the algorithm is fueled to assess a signal and also manage it for effective grading based on a qualitative approach.
In this paper we provide a comprehensive and detailed description of this hybrid approach.
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