Background: Artificial intelligence (AI) provides opportunities to identify the health risks of
patients and thus influence patient safety outcomes. Objective: The purpose of this …

Artificial intelligence (AI) is a transformative technology used in various industrial sectors
including healthcare. In pharmacy practice, AI has the potential to significantly improve …

Bayesian networks (BNs) have received increasing research attention that is not matched by
adoption in practice and yet have potential to significantly benefit healthcare. Hitherto …

Business intelligence (BI) is the process of transforming raw data into useful information for
more effective strategic, operational insights, and decision-making purposes so that it yields …

There has been much research effort expended toward the use of Bayesian networks (BNs)
in medical decision-making. However, because of the gap between develo** an accurate …

Introduction Pharmacovigilance programs protect patient health and safety by identifying
adverse event signals through postmarketing surveillance of claims data and spontaneous …

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

Adverse drug reactions (ADRs) are a major public health concern, causing over 100,000
fatalities in the United States every year with an annual cost of $136 billion. Early detection …

Abstract Purpose Spontaneous reporting systems (SRSs) are used to discover previously
unknown relationships between drugs and adverse drug reactions (ADRs). A plethora of …

An adverse drug event (ADE) is defined as an adverse reaction resulting from improper drug
use, reported in various documents such as biomedical literature, drug reviews, and user …