Articles tagged as 'DataScience'

13 results

Current safety concerns with HPV vaccination
Using adverse event cluster analysis UMC and the Danish pharmacovigilance centre have researched the extent of safety concerns associated with HPV vaccinations.

EHDEN consortium seeking better value from data
Despite great progress, real-world data that could be better exploited to research and improve healthcare systems, services and treatments, for the benefit of patients.

Big data and signal detection at ISoP
ISoP's 15th annual meeting in Prague, Czech Republic, in October 2015 had an unusual theme – Cubism in Pharmacovigilance, inspired by the Czech cubism movement in the early 1900s.

vigiGroup in action – new method identifies groups of related reports
See how UMC’s new clustering algorithm identifies groups of related reports in our new explainer animation.

Expanding sources of evidence for better signal detection – New podcast out now
In this digital age, can pharmacovigilance experts leverage on new types of data to find evidence for signals? Listen to the latest Drug Safety Matters podcast to find out.

Automatic for the people
Deep learning shows promise removing personal identifiers from case reports, according to new work presented by UMC researchers.

Fruitful start for EHDEN-powered signal discovery
In a weeklong groundbreaking study-a-thon with the IMI EHDEN consortium, UMC researchers found longitudinal health data could boost preliminary analysis of drug-event combinations.

Unlocking the power of real-world data – New podcast episode
Real-world data is a rich source of evidence for pharmacovigilance, but there are challenges yet to be faced before unlocking its true potential as a resource.

Found in space – New method reveals related drug and reaction terms
Could natural language processing unlock powerful new methods in pharmacovigilance science? See how a journey through space could lead to a new dimension in case report analysis.

UMC breaks ground in automated coding for safety reports
A new study highlights the gains to be made in time, quality, and consistency from using UMC’s coding engine WHODrug Koda to automate drug coding in post-marketing surveillance.