Generation of correlation hypotheses between Adverse Events (AEs) and NamedEntity Recognition (NER) of drugs in social media and scientific journals usinga machine learning approach

Pharmacovigilance (PV) has evolved and grown more complex over the past 5 to 10 years due to increasing data volumes, evolving regulations, influence of emerging markets and the emerging social media and innovative technological advances.
Fast detection of Adverse Drug Reactions (ADRs) could allow the pharmaceutical industry to anticipate and then to control more efficiently eventual risks associated to taking some medications. There is a clear that the social medias data base is important for continuous and automated ADRs surveillance and it may reduce the number of ADR related potential deaths [1].
The scientific literature review is requires for tracking and identification of risk/benefit ratio of drugs and safety issues.
Adverse Drug Reactions (ADRs)

Faculty Supervisor:

Chahé Nerguizian;Yvon Savaria

Student:

Partner:

Medvalgo Group

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Polytechnique Montréal

Program: