Clinical pharmacology and therapeutics
Feb 27, 2020
Dihydropyrimidine dehydrogenase (DPD)-deficient patients might only become aware of their genotype after exposure to dihydropyrimidines, if testing is performed. Case reports to pharmacovigilance databases might only contain phenotypical manifestatio...
Therapeutic innovation & regulatory science
Dec 28, 2019
There are significant challenges and opportunities in deploying and utilizing advanced information technology (IT) within pharmacovigilance (PV) systems and across the pharmaceutical industry. Various aspects of PV will benefit from automation (e.g.,...
Social media has been identified as a promising potential source of information for pharmacovigilance. The adoption of social media data has been hindered by the massive and noisy nature of the data. Initial attempts to use social media data have rel...
Drug-associated adverse events cause approximately 30 billion dollars a year of added health care expense, along with negative health outcomes including patient death. This constitutes a major public health concern. The US Food and Drug Administratio...
PURPOSE: Adverse event (AE) identification in social media (SM) can be performed using various types of natural language processing (NLP) and machine learning (ML). These methods can be categorized by complexity and precision level. Co-occurrence-bas...
Interventional pharmacology is one of medicine's most potent weapons against disease. These drugs, however, can result in damaging side effects and must be closely monitored. Pharmacovigilance is the field of science that monitors, detects, and preve...
Identifying medical persona from a social media post is critical for drug marketing, pharmacovigilance and patient recruitment. Medical persona classification aims to computationally model the medical persona associated with a social media post. We p...
Computer methods and programs in biomedicine
Apr 30, 2019
BACKGROUND AND OBJECTIVE: Automatic extraction of adverse drug effect (ADE) mentions from biomedical texts is a challenging research problem that has attracted significant attention from the pharmacovigilance and biomedical text mining communities. I...
Machine learning, especially deep learning, has the predictive power to predict adverse drug reactions, repurpose drugs and perform precision medicine. We provide a background of machine learning and propose a potential high-performance deep learning...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.