Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
OBJECTIVE: This review presents Darwinian nanomedicine as an artificial intelligence (AI)-enabled drug delivery strategy that applies Darwinian evolutionary principles as a computational and engineering analogy. Rather than implying biological evolution of nanoparticles, the framework employs iterative cycles of variation, selection, adaptation, and computational inheritance to optimize nanopartic...
Pancreatic ductal adenocarcinoma (PDAC) remains a formidable malignancy characterized by late diagnosis, high recurrence rates, and pronounced chemoresistance. While nanoparticle-based drug delivery systems (NDDS) offer theoretical advantages over conventional therapies, their clinical translation in PDAC has been severely limited. The dense desmoplastic stroma, elevated interstitial fluid pressur...
Developing practical aqueous zinc metal batteries is crucial for safe grid energy storage. However, zinc anode imposes severe interfacial mass transfe...
Existing medical image segmentation (MedISeg) models predominantly rely on convolutional neural networks (CNNs) and Transformer architectures. However...
BACKGROUND: High-quality problem-based learning (PBL) during internship is resource-intensive and difficult to scale without consistent facilitation. ...
Orthodontic treatment is delivered in increasingly diverse clinical and digital environments, yet outcomes continue to depend on patients' understandi...
PURPOSE OF REVIEW: This review surveys recent advances in artificial intelligence-guided small molecule discovery and gene therapy, with a focus on ge...
Rapid and reliable detection of biological agents is crucial in both military and civilian contexts. Here, we present a promising field-deployable app...
BACKGROUND: Psychiatry needs objective technological tools to address global staffing shortages, stigma, and other systemic challenges. An AI-based sy...
STUDY OBJECTIVE: To apply Autor's labor economics task framework to classify emergency physician tasks by automation susceptibility and map current ar...
PURPOSE: To develop and evaluate an unsupervised domain adaptation (UDA) framework for glaucoma classification from fundus images that improves the ge...
This study integrates deep reinforcement learning (DRL) with lean management for renewable energy project scheduling. The problem is formulated as a c...
AimTo gather nurses' perceptions nursing hematologic management on patients undergoing CAR-T cell therapy. A combined approach using statistical analy...
Material Recovery Facilities (MRFs) are essential to municipal recycling infrastructure, but face difficulties in sorting due to the growing complexit...
BACKGROUND: Prior authorization (PA) is intended to support appropriate use and spending of services and medications, yet 1 in 6 insured adults report...
A large academic medical center in the Pacific Northwest addressed perioperative staffing challenges by implementing a workflow with application of AI...
BACKGROUND: Call abandonment is a critical barrier to patient access in health care call centers; yet, predictive modeling efforts are limited by stri...
Artificial intelligence (AI) is accelerating antimicrobial peptide (AMP) discovery, but prediction-centered workflows often overlook dataset redundanc...
INTRODUCTION: Polyendocrine Metabolic Ovarian Syndrome (PMOS) is an endocrine disorder characterized by metabolic dysfunction, hormonal imbalance, inf...
OBJECTIVE: To examine Inpatient Rehabilitation Facilities, market, and regional characteristics associated with operational AI adoption across three f...