Latest AI and machine learning research in work force for healthcare professionals.
BACKGROUND: The increasing documentation burden on physicians is a significant contributor to burnout and decreases in care quality. Artificial intelligence (AI) has been proposed as a solution to reduce documentation burden in clinical care, but there are very limited data on its use in the inpatient and intensive care unit (ICU) environments. OBJECTIVE: This pilot study aimed to explore the feas...
Rural small and micro enterprises (RSMEs) struggle to borrow, and the reason is rarely a shortage of willing lenders. It is that the information a lender would normally rely on is missing, informal, or simply not written down. Conventional scorecards, built for firms with clean books, tend to falter here, where the data are heterogeneous, riddled with gaps, and shaped by nonlinear risk. We build a...
Understanding the mechanisms driving aboveground biomass (AGB) variation in forest ecosystems is essential for biodiversity conservation and climate-c...
AIMS: To define rates of diagnostic image acquisition, clinical drivers of image quality and the learning curve for artificial intelligence (AI)-guide...
Generative artificial intelligence (AI) has rapidly advanced over the past decade in the field of drug discovery, particularly for the de novo design ...
PURPOSE: To examine the impact of artificial intelligence (AI) on radiologists' workload and economic outcomes by synthesizing current evidence on wor...
OBJECTIVES: This pilot study investigated whether occlusal force distribution measured by T-Scan can be predicted from intraoral scan images using dee...
The integration of Artificial Intelligence (AI) into modern medicine has revolutionised diagnostic accuracy, yet it generates a critical ethical dilem...
Antimicrobial resistance in aquaculture threatens environmental and public health, but the risk of ARGs cannot be inferred from abundance alone; host ...
In this work, we introduce Progressive Growing of Patch Size (PGPS), an automatic curriculum learning approach for 3D medical image segmentation. Curr...
BACKGROUND: Nurse burnout is a pervasive global problem. Cognitive behavioral therapy (CBT) has been shown to reduce burnout; however, most digital CB...
BACKGROUND: Informal caregivers of people living with dementia often experience high rates of caregiver burnout while providing care. Although there a...
BACKGROUND: Operating room (OR)-to-intensive care unit (ICU) handoffs are among the most complex and high-risk communication events in perioperative c...
BACKGROUND: Inequitable and time-consuming shift scheduling contributes to nurse burnout, dissatisfaction, and turnover. In Taiwan, annual nurse turno...
BACKGROUND: Clinician burnout has reached crisis levels in emergency medicine, with clinical documentation burden identified as a central contributing...
The paper analyzes the cross-region knowledge transfer characteristics of selected state-of-the art deep learning-based building vectorization methods...
Due to the scarcity of expert-annotated data, Semi-Supervised Medical Image Segmentation (SSMIS) has emerged as a promising approach. Many anatomical ...
The increasing integration of artificial intelligence in clinical decision support systems (AI-CDSS) has fueled expectations of more personalized and ...
The global health workforce faces a projected shortage of more than 11 million health workers by 2030, with the most severe shortfalls in low- and mid...
As a vital ecological buffer zone and biodiversity hotspot, the structure and composition of macroinvertebrate communities in estuarine wetlands are u...