Latest AI and machine learning research in hospital-based medicine for healthcare professionals.
OBJECTIVES: To determine whether an artificial-intelligence-driven Clinical Deterioration Index (CDI) could identify geriatric hip-fracture patients at risk of early postoperative complications and to establish an orthopaedic-specific cutoff that identified patients at risk of deterioration. METHODS: Design: Retrospective cohort study. SETTING: Single Level I trauma center. PATIENT SELECTION CRITE...
This article introduces a dataset designed for the detection of partial discharges in transmission power lines using covered conductors through a contact galvanic method, sourced from real environments across 23 different power lines in various locations. Though partially introduced in a Kaggle competition (only 3% of data), its full extent is disclosed here for the first time. The dataset is dist...
INTRODUCTION: Perinatal medication consultation is a core clinical pharmacy service that involves a complex benefit-risk assessment for both maternal ...
RATIONALE & OBJECTIVE: Acute kidney injury (AKI) in research is typically identified using KDIGO criteria based on changes in serum creatinine (SCr) l...
PURPOSE OF THE REVIEW: Artificial intelligence in health is evolving rapidly, and there is a lot of hope that it may improve patient outcomes. The per...
BACKGROUND: Klebsiella pneumoniae complex (Kp) is a relevant neonatal pathogen colonizing preterm infants. While outbreak investigations often focus o...
The rapid fabrication of artificial intelligence-based hardware worldwide is intensifying the electronic waste (e-waste) crisis, threatening ecosystem...
To address the challenges of achieving organic compliance in kitchen wastewater treatment and the high cost of chemical dosing, this study established...
INTRODUCTION: Typhoid intestinal perforation (TIP) remains a significant cause of pediatric morbidity in resource-limited settings, with prolonged hos...
BACKGROUND: Nosocomial infections (NI) in cirrhosis are associated with high mortality but could be preventable. Logistic regression (LR) models have ...
BACKGROUND: Artificial intelligence (AI) offers new methods to improve diagnosis and treatment in mental health. However, its use raises legal and eth...
INTRODUCTION: Dementia imposes significant care and financial burdens on families and countries globally. While high-quality home-based care is crucia...
The rapid evolution of artificial intelligence (AI) and its profound integration with the pharmaceutical industry essentially constitute a process of ...
BACKGROUND: Conversational AI offers scalable mental health support, with large language models (LLMs) enabling personalized interactions. Human-cente...
BACKGROUND: Medication errors remain a leading source of preventable harm in hospitalized patients, contributing to adverse drug events (ADEs), prolon...
OBJECTIVE: To evaluate the predictive utility of the initial lactate-to-albumin ratio (LAR) measured within 24Â h of admission for in-hospital all-caus...
OBJECTIVE: Traditional readmission risk models relying on static discharge data have limited predictive performance and fail to capture patients' reco...
The spine is among the most frequent sites of metastatic disease, with an increasing prevalence, leading to increasing rates of surgical interventions...
BACKGROUND: Postoperative delirium (POD) is a prevalent and serious complication in older surgical patients, linked to prolonged hospitalization, high...
AIM: To explore nurses' lived experiences of a generative artificial intelligence-enabled shift handover innovation. DESIGN: A descriptive phenomenolo...