: Attention-Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity. Traditional diagnostic methods, which depend on subjective assessments, often lack precision. This study evaluates the validity and reliability of a newly developed diagnostic tool, the Distractor-Embedded Auditory Continuous Performance Test (da-CPT), which integrates auditory stimuli with distractors to enhance the clinical utility of ADHD diagnosis.
View Article and Find Full Text PDFBackground: Evidence supporting the benefits of autonomous learning of basic life support, such as rapid outcomes and cost-effectiveness, is increasing. Reports supporting the autonomous learning of cognitive skills in basic life support exist. However, there is currently no report supporting the autonomous learning of psychomotor skills in basic life support.
View Article and Find Full Text PDFBackground: The phenomenon of burnout among healthcare workers during the COVID-19 pandemic is a widespread problem with several negative consequences for the healthcare system. The many stressors of the pandemic have led to an increased development of anxiety and depressive disorders in many healthcare workers. In addition, some manifested symptoms of the so-called postpandemic stress syndrome and the emergence of occupational burnout syndrome, commonly referred to as "COVID-19 burnout.
View Article and Find Full Text PDFIn the field of unmanned systems, the combination of artificial intelligence with self-operating functionalities is becoming increasingly important. This study introduces a new method for autonomously detecting humans in indoor environments using unmanned aerial vehicles, utilizing the advanced techniques of a deep learning framework commonly known as "You Only Look Once" (YOLO). The key contribution of this research is the development of a new model (YOLO-IHD), specifically designed for human detection in indoor using drones.
View Article and Find Full Text PDFThe development of Web 2.0 and the rapid growth of available data have led to the development of systems, such as recommendation systems (RSs), that can handle the information overload. However, RS performance is severely limited by sparsity and cold-start problems.
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