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

Abstract The World Health Organization (WHO) announced the first-ever World Patient
Safety Day on September 17, 2019, which remarks a global campaign to create an …

Background: Adverse events refer to incidents with potential or actual harm to patients in
hospitals. These events are typically documented through patient safety event (PSE) reports …

Objective To evaluate the feasibility of a convolutional neural network (CNN) with word
embedding to identify the type and severity of patient safety incident reports. Materials and …

Mental health challenges such as stress, anxiety and depression are on the rise worldwide.
Health virtual communities (VCs) is a rising paradigm that has proven to be efficient and …

Objective The study sought to evaluate the feasibility of using Unified Medical Language
System (UMLS) semantic features for automated identification of reports about patient safety …

Most research concerning healthcare Artificial Intelligence (AI) has neglected its ecological
validity and human cognition consideration, which can create challenges at the interface …

Artificial intelligence (AI) is intended to help clinicians exercise their professional judgment
in making appropriate decisions for a given patient. Recently, research has exhibited the …

Adverse events in hospitals pose a serious threat to patient care quality and safety globally,
contributing to patient distrust and impacting healthcare facility reputations (1). A significant …

With growing use of machine learning (ML)-enabled medical devices by clinicians and
consumers safety events involving these systems are emerging. Current analysis of safety …