Latest AI and machine learning research in prevention of medical errors for healthcare professionals.
BACKGROUND: Generative artificial intelligence (GAI) has rapidly expanded into health and social care, offering new opportunities for communication, clinical support, and personalized interventions. Long-term care (LTC) represents a critical application area for improved health related quality of life (HRQoL) due to workforce shortages, increasing care complexity, and the need for scalable, person...
Health communication often faces a segmentation-intervention gap: psychographic segmentation identifies meaningful audience profiles, but these profiles are rarely translated into experimentally tested segment-specific messages. This study proposes and tests a segmentation-to-intervention pipeline that integrates Health Belief Model (HBM) diagnostics with generative artificial intelligence (GAI) f...
PURPOSE: Research on vision-language models (VLMs) in the medical field has recently increased. However, while multifaceted evaluation is necessary to...
OBJECTIVE: Automating administrative tasks, such as compiling a patient's medical history, could help general practitioners in their daily work. AI pe...
BACKGROUND: PCLAF (PCNA clamp-associated factor) is a protein involved in DNA replication and DNA repair. Aberrant PCLAF expression has been reported ...
BACKGROUND: Effective communication is crucial for high-quality health care, but systemic barriers still disrupt patient-provider interactions. Resear...
BACKGROUND: Patients undergoing invasive procedures frequently experience anxiety and often have unanswered questions regarding the procedure. Althoug...
A graphene-silicon-based twin-port terahertz (THz) antenna is proposed and investigated in this work. The antenna employs an aperture-coupled asymmetr...
Allostery offers a powerful route to regulate protein function and expands drug discovery beyond the orthosteric paradigm. By acting at sites distinct...
BACKGROUND: Empathic communication in the clinical setting has been associated with improved clinical outcomes, decreased anxiety, and increased patie...
OBJECTIVE: This scoping review aims to identify the current applications of artificial intelligence (AI) in preventive dentistry for primary disease p...
BACKGROUND: Early childhood is a critical developmental period during which exposure to multiple environmental chemicals is common and increasingly re...
Cardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality worldwide, and the burden is particularly severe in low-income and ...
PURPOSE: To examine global research trends in delirium prevention through a bibliometric analysis and provide a structured overview of its development...
As generative AI becomes a standard fixture in graduate education, the pedagogical challenge has shifted from detection to integration. This article d...
Successful deployment of medical artificial intelligence (AI) systems should start with formulating clear goals and understanding organisational workf...
BACKGROUND: Shared decision-making (SDM) is a key element of patient-centered care; however, opportunities for structured and scalable SDM training re...
BACKGROUND: Patients increasingly use large language models (LLMs) to obtain medical information, but the quality of LLM-generated information on comp...
Trigeminal neuralgia (TN) is a debilitating neuropathic pain disorder characterized by sudden, intense facial pain, with diagnosis heavily reliant on ...
BACKGROUND: Data science methods can provide novel and pragmatic approaches for preventing and controlling non-communicable diseases (NCDs) in Africa....