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Validation and Transparency in AI systems for pharmacovigilance: a case study applied to the medical literature monitoring of adverse events. (arXiv:2201.00692v1 [cs.IR])
cs.LG updates on arXiv.org arxiv.org
Recent advances in artificial intelligence applied to biomedical text are
opening exciting opportunities for improving pharmacovigilance activities
currently burdened by the ever growing volumes of real world data. To fully
realize these opportunities, existing regulatory guidance and industry best
practices should be taken into consideration in order to increase the overall
trustworthiness of the system and enable broader adoption. In this paper we
present a case study on how to operationalize existing guidance for validated
AI systems in pharmacovigilance focusing …
ai ai systems arxiv case study events literature monitoring study systems transparency validation