Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
Amyotrophic lateral sclerosis (ALS) requires precise therapeutic monitoring of Edaravone, but current methods lack real-time capability. Herein, we developed a photoelectrochemical (PEC) sensor using a Bi4Ti3O12/BiOBr heterojunction for ultrasensitive Edaravone detection. The heterojunction interface enables Type II band alignment, facilitating efficient charge separation through electron transfer...
Active learning fosters critical thinking, autonomy, and deep learning. Whereas team-based learning (TBL) is common, inquiry-based learning (IBL) offers a more student-centered, inquiry-driven alternative. This study aimed to compare the pedagogical effectiveness of IBL versus TBL in medical education, focusing on academic performance, learner engagement, autonomy, and satisfaction. An innovative ...
BACKGROUND: Intensive Care Unit (ICU) nursing is demanding, requiring advanced clinical decision-making and emergency management skills. Simulation-ba...
PURPOSE: To synthesise the paradigm shift towards precision medicine in orthopaedics, where individual anatomical, biomechanical, molecular and kinema...
This study evaluated three timing strategies for delivering AI assistance in pathological slide diagnosis - pre-diagnosis (triage), during diagnosis (...
PURPOSE: Time-dependent diffusion MRI enables quantification of tumor microstructural parameters useful for diagnosis and prognosis. Nevertheless, cur...
AIM: To examine the perinatal experiences of at-risk mothers and their engagement with mobile-health-based care. DESIGN: A qualitative descriptive stu...
Previous studies on memristive associative neural network circuits have not sufficiently incorporated the effects of spike-rate-dependent plasticity (...
BACKGROUND: Clinical trials face unprecedented challenges including recruitment delays affecting 80% of studies, escalating costs exceeding $200 billi...
In practical industrial scenarios, monitoring data is collected in a streaming fashion under dynamic changes in operating conditions of mechanical sys...
AIMS: To predict nurses' turnover intention using machine learning techniques and identify the most influential psychosocial, organisational and demog...
Photon-counting detector computed tomography (PCD-CT) is an emerging imaging technology that promises to overcome the limitations of conventional ener...
Achalasia is generally considered a progressive condition where esophageal deformity worsens over time; diagnostic delay results in the overdilated an...
Offline reinforcement learning provides the capability to learn a policy only from pre-collected datasets, but its performance is often limited by the...
Artificial intelligence (AI) is rapidly emerging as a transformative force in pediatric nephrology, enabling improvements in diagnostic accuracy, ther...
OBJECTIVES: Domain shift has been shown to have a major detrimental effect on AI model performance however prior studies on domain shift for MRI prost...
The commercialization of lithium‑sulfur (LiS) batteries faces fundamental issues from polysulfide shuttling to inefficient redox kinetics, compounded ...
OBJECTIVES: To explore how artificial intelligence (AI) can improve the clinical and rehabilitation management of knee osteoarthritis (KOA), emphasizi...
WHAT WAS THE EDUCATION CHALLENGE?: Health professions education faces a critical challenge: the volume and complexity of medical knowledge has outpace...
Administrative tasks remain a leading contributor to physician burnout in primary care and hospital settings. Recent advancements in informatics infra...