Hospital-Based Medicine

Assessment of Pain Intensity Using Deep Learning Models in Non-Communicative Intensive Care Patients.

BACKGROUND: Pain is a multifaceted and subjective phenomenon frequently experienced by patients in intensive care units. In non-communicating populations, conventional assessment tools are often inadequate and susceptible to observer bias. Deep learning-based facial analysis has emerged as a promising approach for the objective quantification of observable pain-related behavioural indicators. AIM:...

Machine Learning Interpretability to Assess the Association Between Time in Tight Range and Mortality in Cardiogenic Shock.

BACKGROUND: Cardiogenic shock (CS) is a critical condition of end-organ hypoperfusion with high mortality. Fluctuations in blood glucose (BG) levels may exacerbate cardiovascular instability in critically ill patients. Time In Tight Range (TITR), defined as the percentage of time in the target BG range of 3.9-7.8 mmol/L (70-140 mg/dL), has become an increasingly important index of glycaemic status...

Early Detection of Gallbladder and Biliary Malignancy.

Gallbladder cancer and cholangiocarcinoma are aggressive biliary malignancies with poor prognoses, due to their insidious onset and late-stage diagnos...

An XGBoost-Based Multicenter Model for Predicting HBV-Related Hepatocellular Carcinoma: Development and Validation.

BACKGROUND: The 5-year survival rate for hepatocellular carcinoma (HCC) is stage-dependent, yet existing models lack accuracy in predicting hepatitis ...

Development and Internal Validation of a Machine Learning Model for Predicting Long-Term Opioid Therapy After Hip Fracture Surgery in Older, Opioid-Naïve Adults.

BACKGROUND: Long-term opioid therapy (LTOT) after hip fracture surgery is a common postoperative complication associated with adverse outcomes, yet to...

Interpretable Machine Learning to Anticipate the Diagnostic Yield of EEG in the Emergency department. The EMINENCE study.

INTRODUCTION: Emergent electroencephalography (emEEG) is increasingly employed in the emergency department (ED) for evaluating altered consciousness a...

AI for Hospital Infection Prevention and Control: Real-World Implementation, Impact, and the Gap Beyond Model Development.

BACKGROUND: Artificial intelligence and machine learning (AI/ML) may strengthen hospital infection prevention and control (IPC) through automated surv...

Perspectives from healthcare providers and decision-makers on strategies toward a future hospital: qualitative insights from a group modelling process.

AIM: Planning for a hospital is a complex and dynamic process, traditionally not informed by evidence. A systems thinking approach can be useful in in...

A scoping review of quality prescribing indicators, rules and criteria for primary care.

Medication-related problems (MRPs) place a substantial burden on the healthcare system, contributing to hospital admissions and significant healthcare...

Neural Stem Cell-Derived Extracellular Vesicles: The Next Frontier in Neurological and Neurodegenerative Diseases.

The present manuscript provides a comprehensive overview of neural stem cell (NSC)-derived extracellular vesicles (NSC-EVs( as a cell-free approach to...

Does the Timing of USMLE Step 1 Affect Performance? A Comparison of Pre- and Post-Clerkship Timing in the Pass/Fail Era.

In 2022, Step 1 of the United States Medical Licensing Examination transitioned to pass/fail scoring, removing a major performance-oriented incentive ...

Magnetic Resonance Neurography: Evolution, Technical Foundations, and Future Directions.

ABSTRACT: In the past 20 years, magnetic resonance neurography has evolved from an experimental technique into an essential diagnostic pillar for peri...

Exploratory association between multimodal AI-derived digital biomarkers and in-hospital mortality in adult patients with pneumonia: A proof-of-concept study.

Pneumonia remains a leading cause of in-hospital mortality worldwide. Current prognostic tools such as the IDSA/ATS severity score have meaningful lim...

Systems of Care in Cardiogenic Shock: Team-Based Management, Shock Networks, and Post Discharge Pathways.

Cardiogenic shock (CS) remains the leading cause of mortality in modern cardiac intensive care unit, most often precipitated by acute or chronically d...

Early emergency department decision support for heart failure hospitalization using triage-level unstructured and structured data: a retrospective cohort study.

BACKGROUND: Early identification of patients at risk for heart failure (HF) hospitalization in the emergency department (ED) is challenging because de...

Implementing Artificial Intelligence in Radiology: Design Thinking Road Map.

Despite its promising potential to transform medical care, particularly in the field of medical images, the integration of artificial intelligence (AI...

Clinical AI is Not (Yet) Trustworthy-But It Could Be.

The growing emphasis on trustworthy artificial intelligence (AI) in health care reflects a shift away from models optimized for predictive performance...

Are machine learning models superior to logistic regression models to predict 30-day mortality post-hip fracture surgery?

Hip fractures represent a significant global health burden, with high mortality rates. Accurate prediction of 30-d postoperative mortality is instrume...

The application of digital technology in nursing quality management: a scoping review.

BACKGROUND: Digital technology integrates information and communication tools such as electronic health records, wearable devices, and artificial inte...

Post-operative delirium risk estimation and assessment with machine learning: development and validation of the Open-DREAM Model: A peri-operative dataset analysis.

BACKGROUND: Postoperative delirium (POD) is a common and serious complication in older surgical patients, associated with increased morbidity, prolong...