The value of social media data for Adverse Drug Reaction (ADR) monitoring is actively investigated. While social media provide a vast amount of data, these data are hard to analyse due to their unstructured nature and lack of credibility. Despite these challenges, social media have been identified as a potentially useful data source, potentially able to “strengthen” the evidence for new ADRs. To this end, PVClinical project aims to build a platform facilitating the investigation of multiple heterogeneous data sources, including social media, to support pharmacovigilance (PV) processes, both in the clinical environment and beyond. In this study, we present the PVClinical Twitter workspace, also highlighting the rationale behind the main design choices, while also discussing the respective challenges.
Transfer Learning (TL) is an approach which has not yet been widely investigated in healthcare, mostly applied in image data. This study outlines a TL pipeline leveraging Individual Case Safety reports (ICSRs) and Electronic Health Records (EHR), applied for the early detection Adverse Drug Reactions (ADR), evaluated using of alopecia and docetaxel on breast cancer patients as use case.
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