At present, in pharmacology one of the most serious problems is counterfeit drugs. The
Health Research Funding organization reported that in developing countries, nearly 10 …

Background Text mining and natural language processing of clinical text, such as notes from
electronic health records, requires specific consideration of the specialized characteristics of …

Electronic Health Records have proven to be indispensable yet continue to present a host of
problems. One of the most pressing concerns is how to share patient information freely and …

Abstract Background Adverse drug events (ADEs) as well as other preventable adverse
events in the hospital setting incur a yearly monetary cost of approximately $3.5 billion, in …

Counterfeit drugs is an expanding serious issue associated with the healthcare industry
which causes extreme threats to the society. The traceability of the drugs throughout the …

Electronic patient records are produced in abundance every day and there is a demand to
use them for research or management purposes. The records, however, contain information …

A variety of deep learning architectures have been developed for the goal of predictive
modelling in regards to detecting health diagnoses in medical records. Several models have …

This article presents experiments with pseudonymised Swedish clinical text used as training
data to de-identify real clinical text with the future aim to transfer non-sensitive training data …

We study the problem of detecting adverse drug events in electronic health records. The
challenge is this work is to aggregate heterogeneous data types involving lab …

The COVID-19 vaccine program brings a limelight on how supply chains can be made safer
and more reliable. In developing economies, one out of ten medical products are either of …