Hospital-Based Medicine

Early laboratory-based differentiation of severe influenza pneumonia and influenza-associated encephalopathy in children using a multi-model, stability-aware machine-learning workflow: a single-center retrospective cohort study.

BACKGROUND: Influenza-associated encephalopathy and acute necrotizing encephalopathy (ANE) are rare but devastating complications of pediatric influenza, and early differentiation from severe pneumonia without neurological involvement is challenging at admission. We aimed to develop and internally validate an early prediction model to distinguish severe influenza A pneumonia from influenza-associa...

One year quality of life outcomes in critically ill children: a multicenter prospective cohort study.

BACKGROUND: Survivors of pediatric intensive care often experience prolonged morbidity, but recovery trajectories and features associated with impairment in general PICU populations remain uncertain. We aimed to explore the trajectory of health-related quality of life (HRQoL) and fatigue in critically ill children over the first year following PICU discharge, and to identify baseline and PICU fact...

Physics-Informed Graph Learning for Spatially Contiguous and Capacity-Constrained Hospital Service Area Delineation.

Delineating Hospital Service Areas (HSAs) is critical for healthcare resource allocation and policymaking. However, existing methods struggle to simul...

Development of Machine Learning Models to Predict Candidemia in Hospitalized Adult Patients.

PURPOSE: We aimed to develop a generalizable machine learning model that leverages electronic medical record (EMR) data to predict candidemia using in...

Smartphone-Based Pupillometry for Noninvasive Detection of Elevated Intracranial Pressure in Nepali Acute Brain Injury Patients: A Pilot Study.

BACKGROUND: Intracranial hypertension is a life-threatening complication of acute brain injuries such as traumatic brain injury (TBI), subarachnoid he...

Development, Implementation, and Preliminary Results of a Novel Social Network for Rare Disease Communities: Mixed Methods Study.

BACKGROUND: Rare diseases affect approximately 20 million Europeans, presenting unique challenges such as delayed diagnoses, limited therapies, and si...

Transforming Psoriatic Disease Care Through Innovation and Real-World Data: GRAPPA 2025 Soapbox Highlights.

The Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) 2025 annual meeting, held in Bogotá, Colombia, featured soapbox pr...

Admission blood pressure percentiles and in-hospital mortality in pediatric heart failure: a multicenter retrospective cohort study.

BACKGROUND: Pediatric heart failure (PHF) carries a high mortality burden, yet the prognostic value of admission blood pressure (BP) remains poorly de...

Concordance of Large Language Model Recommendations with Multidisciplinary Heart Team Decisions in Coronary Revascularization and Aortic Valve Intervention: A Systematic Review and Pooled Analysis.

INTRODUCTION: The multidisciplinary heart team (HT) remains the cornerstone of decision-making for complex cardiovascular disease. Large language mode...

Machine learning to predict plasma-based CO2 conversion in dielectric barrier discharge reactors.

Plasma-based CO2 conversion is an emerging defossilization technology that converts a potent greenhouse gas into valuable chemical feedstocks, yet its...

Data-driven decision support in hospital resource planning: an artificial intelligence-based model proposal for emergency department demand.

BACKGROUND: The sustainability of service quality in healthcare systems is directly related to accurate resource planning, especially in emergency dep...

Generative artificial intelligence for inpatient documentation summarization: mixed-methods quality assessment and early real-world experience.

OBJECTIVE: We evaluated the quality and adoption of a large language model (LLM)-based summarization tool for ongoing hospital care. MATERIALS AND MET...

Machine Learning and Deep Learning Models for Predicting Future Falls in Community-Dwelling Older Adults: Systematic Review and Meta-Analysis of Longitudinal Evidence.

BACKGROUND: Machine learning (ML) and deep learning (DL) show promise for fall risk prediction, but prior reviews focused mainly on real-time fall det...

Application of a conversational AI system for voice-interactive history taking in neurosurgical patients.

BACKGROUND: ccurate and structured medical history taking is essential in neurosurgical practice, but repetitive inpatient interviews can be time-cons...

Comparative accuracy of a predictive algorithm versus cardiologist assessment for 90-day readmission in decompensated chronic heart failure.

BACKGROUND: Heart failure is a leading cause of hospital readmission globally. Few studies have compared the performance of artificial intelligence-ba...

Machine learning using PROFUND components for 30-day readmission prediction in multimorbid patients: a prospective multicentre study.

Early hospital readmission in multimorbid patients remains a major clinical challenge. Although risk stratification tools are widely used, predictive ...

Explainable AI in hospital clinical decision support systems: A scoping review of healthcare professionals' perspectives.

Explainable Artificial Intelligence (XAI) has the potential to enhance clinical decision support (CDS) systems however, it remains unclear how XAI sys...

Blood biomarker trajectories in ICU-directed prediction models - A scoping review.

BACKGROUND: Despite advanced analytical methods and increasing data availability, most intensive care unit (ICU) prediction models rely on static meas...

EXPRESS: Artificial Intelligence in Diabetes Care: Toward Precision Diagnosis and Personalized Management.

AimsDiabetes mellitus is a global health challenge requiring innovative solutions for early diagnosis, personalized treatment, and ongoing management....

Prediction of postoperative desaturation and bradycardia in neonates undergoing laparoscopic inguinal hernia repair: a retrospective cohort study.

BACKGROUND: Ex-premature infants have a high risk of postoperative apnea and bradycardia. This study aimed to develop a predictive model for postopera...