Administrative and medical processes of the healthcare organizations are rapidly changing
because of the use of artificial intelligence (AI) systems. This change demonstrates the …

We review data mining and related computer science techniques that have been studied in
the area of drug safety to identify signals of adverse drug reactions from different data …

Recent semi-supervised anomaly detection methods that are trained using small labeled
anomaly examples and large unlabeled data (mostly normal data) have shown largely …

Introduction: With increasing availability, the use of healthcare databases as complementary
data source for drug safety signal detection has been explored to circumvent the limitations …

With greater impetus on broad postmarket surveillance, the Voice of the Customer (VoC) has
emerged as an important source of information for understanding consumer experiences …

Background: Many factors that directly or indirectly cause adverse drug reaction (ADRs)
varying from pharmacological, immunological and genetic factors to ethnic, age, gender …

Post-marketing detection and surveillance of potential safety hazards are crucial tasks in
pharmacovigilance. To uncover such safety risks, a wide set of techniques has been …

Fraud detection for online banking is an important research area, but one of the challenges
is the heterogeneous nature of transactions data ie a combination of numeric as well as …

Since adverse drug reactions (ADRs) represent a significant health problem all over the
world, ADR detection has become an important research topic in drug safety surveillance …

Adverse event detection is critical for many real-world applications including timely
identification of product defects, disasters, and major socio-political incidents. In the health …