Hospital-Based Medicine

Shift-Specific Patterns of Nursing Workloads in the Emergency Department: AI Powered Analysis.

AIM: To identify and differentiate workload patterns across shifts and to provide evidence for optimizing nursing workforce allocation in emergency departments: DESIGN: A cross-sectional study. METHODS: Real time data were collected from an emergency department in a general hospital in Seoul, South Korea, between October 30, 2023 to October 24, 2024. Smartphones, beacons, and smartwatches were use...

Evaluation of two large language models for intensive care unit discharge decisions: a prospective observational cohort study.

BACKGROUND: The aim of this study was to evaluate the effectiveness of two general-purpose Large Language Models (LLMs), ChatGPT and Gemini, in predicting Intensive Care Unit (ICU) discharge decisions (discharge vs. non-discharge). By comparing their outputs with decisions made by ICU physicians, we sought to determine the alignment of AI-generated recommendations with expert clinical judgment and...

Machine Learning-Based Prediction Model for 30-Day Emergency Department Revisits in a Medically Underserved Tertiary Hospital: Formative Retrospective Cohort Study.

BACKGROUND: Emergency department (ED) revisits are critical quality indicators, particularly in medically underserved areas, where traditional predict...

An integrated computational-experimental approach identifies Malate Synthase G as therapeutic target to disrupt carbon metabolism in chronic Pseudomonas aeruginosa infection.

Pseudomonas aeruginosa is a leading cause of nosocomial infections, particularly in individuals with a compromised immune system. Due to its strong ad...

Creation of an mHealth Infrastructure to Support the Development and Delivery of mHealth Interventions: Protocol for Demonstration Projects Addressing Smoking Cessation in Cancer Care.

BACKGROUND: Cancer remains a leading cause of morbidity worldwide. To reduce this burden, scalable, effective approaches are needed to address modifia...

Why are rural hospitals closing in the U.S.? Predictors identified using explainable machine learning.

OBJECTIVE: Rural hospital closures in the U.S. reduce access to essential healthcare services and worsen health and economic outcomes in rural communi...

Video-based detection of Delirium in hospitalized adults.

Delirium, a dynamic neuropsychiatric condition associated with morbidity and mortality, remains underdiagnosed due to reliance on subjective, intermit...

Improving healthcare professionals' usage of artificial intelligence-powered risk recommenders through enhancement of trust and acceptance: a rapid realist review protocol.

INTRODUCTION: Healthcare professionals working in busy hospital environments are expected to make multiple back-to-back critical decisions related to ...

Improving the impact of medical student research through structured mentorship: a clinical research enterprise model.

PROBLEM: Medical student research engagement is increasingly important in residency selection and professional development, yet structured, longitudin...

Hydrodynamic investigation of acoustic bubble-surface interactions on nanoarray-coated fins for microelectronic cooling with machine learning-based analysis.

This study presents a novel phase-change cooling strategy that synergistically integrates acoustofluidic bubble dynamics with nanoarray-coated micropi...

Language barriers, mobility, and health equity: clinical risks, economic burden, and policy options for universal language access.

BACKGROUND: International mobility has intensified routine contact between health systems and patients who do not speak the dominant language of care....

Turning Compliance Into Action: An Augmented Intelligence-Enabled Framework for Advocacy Organizations to Drive Population Health Improvement.

Community Health Needs Assessments (CHNAs), mandated by the Affordable Care Act for tax-exempt hospitals, represent an underutilized yet rich data sou...

Review of systemic therapy in HCC with an approach to response assessment in clinical practice.

Systemic therapy for hepatocellular carcinoma (HCC) has undergone rapid transformation over the past decade, significantly expanding treatment options...

AI-assisted case-based learning and flipped classroom to improve clinical decision-making: a randomized controlled trial in reproductive medicine.

BACKGROUND: Efficient training of reproductive medicine clinicians is critical in the context of declining global fertility and increasing infertility...

Development and Validation of an Integrated Artificial Intelligence-Powered Clinical Decision Support Application for Cardiac Critical Care: Combining Coagulation Management, Blood Gas Analysis, Mechanical Ventilation, Hemodynamic Assessment, and Extracorporeal Membrane Oxygenation.

This study describes the development and preliminary validation of an integrated clinical decision support application (Cardiac Critical Care Advisor ...

Machine Learning-Based Periprocedural Prediction Model for No-Reflow Risk After Percutaneous Coronary Intervention in Patients With Acute Coronary Syndrome.

Coronary no-reflow (NR) after percutaneous coronary intervention (PCI) predicts adverse prognosis in patients with acute coronary syndrome (ACS). This...

Histopathology: An investigation so valuable but often neglected in orthopaedic infections.

The incidence of osteoarticular infections is steadily increasing, driven by rising road traffic injuries, greater longevity, increasing comorbidities...

Third-party governance and artificial intelligence for diabetes management in primary health care, China.

PROBLEM: Fragmented primary health care in China fails to tackle the growing burden of noncommunicable diseases. Despite substantial investment, fewer...

Improving Clinical Efficiency Using Artificial Intelligence Scribe for Documentation (ICE-AID Study): A Retrospective-Prospective Cohort Study at a Quaternary Children's Hospital and Health Service.

AIM: To evaluate the impact of an artificial intelligence medical scribe (AIMS) on clinical documentation efficiency, document quality, clinician-pati...

Multimodal GPT-5 for Predicting Poor Functional Outcomes After Intracerebral Hemorrhage in the Emergency Department: Validation Study.

BACKGROUND: In the emergency department, rapid prognostic assessment of patients with intracerebral hemorrhage (ICH) is essential for guiding early ma...