Identification of valid case reports from digital social media with the help of machine learning

Abstract

Social media becomes a novel source for information about pharmacovigilance (PV) and patient perceptions on adverse events. The main questions remain on the supplement routine of social media to provide PV surveillance. This research work has the objectives to find out whether the social media data assessment can determine the new signals, recognized signals from routine PV, recognized signals earlier and certain problems such as patients perceptions and quality issues. In addition, the task is to obtain the number of posts with similarity to AEs (proto- AEs) and the classifications/forms of products that receive the advantage from social media data assessment. Worldwide, adverse drug reactions (ADRs) is the severe menace for public health leads to sickness, frailty or even death. Up to now, few countries create a framework to guide the post market drug safety strategy in place of emergent consent to pharmaceuticals globally and emerging trend to gather information including therapeutic record in the post-market rather than premarket time. Such crisis involves a novel hypothetical concept as pharmacovigilance . It consists the entire governing structures, policy instruments and institutional authority like the capability to perform, employ and execute the processes, rules, regulations and guidelines. These can handle the entire endorsed social interests related with the patient s safety and protection from ADRs. newline