Latest AI and machine learning research in nursing for healthcare professionals.
This study aimed to assess university nursing students' knowledge and perceptions of open, laparoscopic, and robotic surgery applications. A simultaneous sequential nested quantitative-qualitative hybrid research method design was conducted. The sub-sample for the qualitative phase was conducted with 35 nursing students using the maximum variation sampling strategy with 423 nursing students studyi...
BACKGROUND: The design and integration of technology within inpatient hospital rooms has a critical role in supporting nursing workflows, enhancing provider experience, and improving patient care. As health care technology evolves, there is a need to design "future-proofed" physical environments that integrate technology in ways that support workflows and maintain clinical performance. Assessing h...
BACKGROUND: Several strategies have been proposed to increase chronic cognitive impairment (CI) screening in the emergency department (ED). Our goal w...
AIM: To assess innovation skills and attitudes toward artificial intelligence BACKGROUND: The rapid advancement of modern healthcare technologies nece...
BACKGROUND: The CONCERN Early Warning System (CONCERN EWS) is an artificial intelligence based clinical decision support system (AI-CDSS) for predicti...
Disparity among gender and ethnicity remains an issue across medicine and health science. Only 26%-35% of trainee radiologists are female, despite mor...
BACKGROUND: Nurse scheduling is a complex challenge in health care, impacting both patient care quality and nurse well-being. Traditional scheduling m...
AIM: To combine the Job Demand-Resource (JD-R) model with machine learning (ML) techniques to identify the key factors affecting job burnout (JB) amon...
BACKGROUND: The integration of generative artificial intelligence (GAI) into nursing education raises concerns owing to nursing's strong emphasis on h...
BACKGROUND: Assessment of the initial medical history data for pregnant women is an essential component of nursing training. Therefore, understanding ...
As in many other sectors, artificial intelligence has an impact on health. Artificial intelligence anxiety may occur because of a lack of knowledge ab...
Machine-learning (ML) models have the potential to transform health care by enabling more personalized and data-driven clinical decision making. Howev...
The rapid advancements of artificial intelligence (AI) in healthcare have triggered a significant literacy gap among nursing professionals, raising co...
This paper explores how artificial intelligence (AI) is being woven into precision medicine for neuro-oncology, highlighting its ethical, clinical, an...
Parkinson's Disease (PD), a frequently diagnosed neurodegenerative condition, poses a major global challenge. Early diagnosis and intervention are cru...
OBJECTIVES: This study evaluated the impact of an electronic health record (EHR) system enhanced with artificial intelligence and machine learning (EH...
Nurses play a crucial role in suicide prevention, yet the integration of artificial intelligence and machine learning technologies into nursing practi...
AIM: This paper provides a scoping review of the literature on prehospital emergency mixed reality (MR) nursing education and explores the impact of M...
OBJECTIVES: Large language models (LLMs) are increasingly used in healthcare, with the potential for various applications. However, the performance of...
BACKGROUND: As we advance into the digital era, the latest challenge in smartphone technology is integrating artificial intelligence applications, whi...