International journal of environmental research and public health
Aug 20, 2020
The current study examined the predictive ability of discrimination-related variables, coping mechanisms, and sociodemographic factors on the psychological distress level of Korean immigrants in the U.S. amid the COVID-19 pandemic. Korean immigrants ...
Modern societies are exposed to a myriad of risks ranging from disease to natural hazards and technological disruptions. Exploring how the awareness of risk spreads and how it triggers a diffusion of coping strategies is prominent in the research age...
OBJECTIVE: To employ machine learning algorithms to examine patterns of rumination from RDoC perspective and to determine which variables predict high levels of maladaptive rumination across a transdiagnostic sample.
BACKGROUND: Informed estimates claim that 80% to 99% of alarms set off in hospital units are false or clinically insignificant, representing a cacophony of sounds that do not present a real danger to patients. These false alarms can lead to an alert ...
We utilized a data-driven, unsupervised machine learning approach to examine patterns of peripheral physiological responses during a motivated performance context across two large, independent data sets, each with multiple peripheral physiological me...
The study examines employability attributes as psychological mechanisms that explain the link between the career adaptation concerns and self-perceived employability of a sample of professionally qualified knowledge workers (N = 404). A cross-section...
OBJECTIVE: This study aimed to establish and assess the Back Propagation Neural Network (BPNN) prediction model for suicide attempt, so as to improve the individual prediction accuracy.
INTRODUCTION: Intravenous insertion (IVI) is a very common procedure in the emergency department (ED). IVI is often painful and stressful for both children and their families. Currently, distraction therapy is not used as a standard of care for IVI i...
OBJECTIVE: Error-related potentials (ErrP) have been proposed as an intuitive feedback signal decoded from the ongoing electroencephalogram (EEG) of a human observer for improving human-robot interaction (HRI). While recent demonstrations of this app...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.