Background Free-text descriptions in electronic health records (EHRs) can be of interest for
clinical research and care optimization. However, free text cannot be readily interpreted by a …

Introduction: Artificial intelligence (AI) based tools offer new opportunities for
pharmacovigilance (PV) activities. Nevertheless, their contribution to PV needs to be tailored …

The use of natural language processing (NLP) methods and their application to developing
conversational systems for health diagnosis increases patients' access to medical …

Medical data annotation requires highly qualified expertise. Despite the efforts devoted to
medical entity linking in different languages, available data is very sparse in terms of both …

Background: Preventing adverse drug reactions (ADRs) is imperative for the safety of the
people. The problem of under-reporting the ADRs has been prevalent across the world …

Background Adverse drug reactions (ADRs) are estimated to be the fifth cause of hospital
death. Up to 50% are potentially preventable and a significant number are recurrent …

Background: High-quality adverse drug reaction (ADR) reports are essential for conducting
drug safety monitoring in pharmacovigilance. The study aim was to assess the current …

Time is a vital facet of every human activity. Data warehouses, which are huge repositories
of historical information, must provide analysts with rich mechanisms for managing the …

Background and objective Endometriosis and adenomyosis are two common diseases that
impair women's health, and dienogest is one of the pharmacologic treatments which is the …

Objective Combining text mining (TM) and clinical decision support (CDS) could improve
diagnostic and therapeutic processes in clinical practice. This review summarizes current …