Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
Continuous, real-time, and accurate monitoring of human physiological signals is crucial for proactive healthcare and chronic disease management. Traditional rigid sensors, however, face limitations in mechanical compatibility, signal fidelity during dynamic activities and long-term wearability. This review summarizes the recent advancements in liquid metal (LM)-based flexible sensors for human he...
BACKGROUND: The integration of artificial intelligence (AI) into urological robotic surgery is currently in a dynamic phase of development and validation. Minimally invasive, standardized, and video-based procedures create highly data-rich operative environments with clearly defined workflow steps, thereby providing ideal conditions for the development of AI-based systems. OBJECTIVE: The objective...
Hand hygiene (HH) is essential for preventing healthcare-associated infections, yet conventional monitoring approaches primarily capture event occurre...
BACKGROUND: The reliability of general-purpose large language models (LLMs) for complex clinical tasks in specialized domains such as microsatellite i...
Individuals with schizophrenia demonstrated impaired inhibitory control and apathy symptoms, which are characterized by a reduction in self-initiated ...
Humic substances strongly influence the environmental behavior of toxic metals, but the molecular basis by which compositionally similar humic systems...
The rapid integration of generative artificial intelligence (AI) into academic and professional workflows is reshaping human participants research. Wh...
The management of febrile neutropenia (FN) in oncohematological patients is undergoing a paradigm shift driven by a deeper understanding of patients' ...
High-performance dielectric materials are strategically vital for post-Moore microelectronics, high-power electrostatic capacitors, and flexible advan...
The growing demand for brain-inspired computing systems has intensified research into energy-efficient, scalable, and adaptive hardware that mimics bi...
BACKGROUND: Large language models (LLMs) have shown substantial promise in patient-trial matching, but most published studies still evaluate the perfo...
BACKGROUND: Substance use disorder (SUD) remains a major public health crisis in the United States, with significant challenges in treatment access, r...
PURPOSE: The integration of artificial intelligence (AI) into prosthodontics represents a paradigm shift in the design and fabrication of removable pa...
OBJECTIVES: To elicit stated preferences and willingness-to-pay (WTP) for artificial intelligence (AI)-enabled blended care in type 2 diabetes mellitu...
Biomarker research for cancer diagnosis and prognosis has rapidly expanded technologically and thematically, along with advancements in molecular diag...
With the widespread application of artificial intelligence in recruitment, algorithmic bias issues have become increasingly prominent, seriously threa...
BACKGROUND: Advanced and recurrent cervical cancer (CC) remains a clinical challenge due to limited therapeutic options and a poor 5-year survival rat...
School attendance is a fundamental prerequisite for children's and adolescents' academic, social, and personal development. Yet, despite decades of re...
The high rate of increase in the deep learning tasks as well as heterogeneous computing systems necessitates compilers that achieve low compile time a...
Nanomedicine offers powerful opportunities to overcome the pharmacokinetic and microenvironmental limitations of conventional chemotherapy, particular...