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  "Title": "Bayesian Model Selection in Logistic Regression for the\nDetection of Adverse Drug Reactions",
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  "Author": "Matthieu Marbac and Mohammed Sedki",
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  "Description": "Spontaneous adverse event reports have a high potential\nfor detecting adverse drug reactions. However, due to their\ndimension, the analysis of such databases requires statistical\nmethods. We propose to use a logistic regression whose sparsity\nis viewed as a model selection challenge. Since the model space\nis huge, a Metropolis-Hastings algorithm carries out the model\nselection by maximizing the BIC criterion.",
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