Hospitalists

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 performance is often limited. The PROFUND index captures frailty, functional dependence, and social vulnerability, but its role in predicting 30-day readmission is unclear. In this prospective multicentre cohort study, multimorbid patients admitted t...

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 postoperative desaturation and bradycardia in infants who underwent laparoscopic inguinal hernia repair (IHR) under general anesthesia based on identified risk factors. METHODS: The retrospective cohort included infants who underwent laparoscopic IHR under ge...

Deep-learning time-series anomaly detection of acute kidney injury from creatinine-eGFR trajectories in the ICU.

Acute kidney injury (AKI) is common in the intensive care unit (ICU), and fixed creatinine thresholds may miss clinically relevant dynamics. We tested...

Interpretable machine learning for predicting in-hospital mortality in COPD ICU patients: a rigorous validation across time and geography.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a common reason for admission to the intensive care unit (ICU), where accurate risk strati...

Artificial intelligence for predicting hospital admissions from the emergency department: a prospective, quasi-experimental study.

The use of certain artificial intelligence (AI) tools may improve hospital operational efficiency, in particular in overcrowded emergency departments ...

CT-based radiomic markers to predict late-onset seizures after traumatic brain injury.

Post-traumatic epilepsy (PTE) is a major long-term complication of traumatic brain injury (TBI), but early risk prediction remains imprecise. Radiomic...

A deep complementary learning framework for surface water temperature forecasting.

Water temperature plays a pivotal role in shaping riverine ecosystems, exerting significant influence on a range of water quality parameters. However,...

Machine Learning Prediction for 6-Month Outcomes in Traumatic Cerebral Venous Sinus Thrombosis.

This study developed and externally validated a multicenter machine learning framework to predict 6-month poor functional outcome (modified Rankin Sca...

AI-enhanced system dynamics simulation for sustainable urban development under water constraints: A case study of Langfang, China.

Water-scarce cities undergoing rapid urbanization must sustain economic growth while complying with stringent water-resource and environmental constra...

Predicting length of stay in the pediatric intensive care unit at a tertiary center in Saudi Arabia using machine learning.

BACKGROUND: Prolonged stay in pediatric intensive care units (PICUs) is associated with increased mortality risk, elevated healthcare costs, and dimin...

From Lumen to Myocardium With Artificial Intelligence: A Clinician's Guide to Comprehensive Cardiac CT.

Coronary artery disease assessment has long focused on stenosis severity, yet luminal narrowing alone fails to capture ischemic burden, plaque vulnera...

Validation of a machine learning model for predicting early deterioration in the emergency department.

Early recognition of patients at risk for deterioration in the emergency department (ED) is critical for patient safety. Traditional early warning sco...

Recent progress in the effects and mechanisms of non-thermal technologies on alleviating food allergy.

Food allergy is a big concern in food safety. Thermal processing is an effective approach to tackle it, but the method might significantly diminish th...

Intelligent optimization of micro-electrical discharge machining of aluminum nitride ceramics using nano abrasive zirconium oxide-enhanced biodegradable dielectric.

This study explores the use of nano-enhanced Canola Oil Methyl Ester (COME) formulated with 0.5 wt% of zirconium oxide (ZrO2) nanoparticles as a biode...

Cumulative stress hyperglycemia ratio exposure and dynamic trajectories reveal prognostic determinants of acute hyperlipidemic pancreatitis: an 5-year cohort study.

BACKGROUND: The stress hyperglycemia ratio (SHR) and glycemic variability (GV) both reflect acute glycemic fluctuations, with established roles in car...

Early identification of high-risk individuals for mortality after lung transplantation: A retrospective cohort study with topological feature engineering.

Lung transplantation remains the only definitive treatment for end-stage respiratory failure; however, it has substantial post-operative mortality ris...

Understanding how language barriers in the paediatric emergency care setting influences safety of care delivery: a scoping review.

BACKGROUND: Communication in a family's primary language can support safe care. Vital steps within the care delivery process are contingent on success...

Predictive analysis of health-related quality of life trajectories in older patients with chronic pain based on explainable machine learning models.

BACKGROUND: Health-related quality of life (HRQoL) is a vital indicator of evaluating care outcomes and prognosis, yet little is understood about its ...

Artificial Intelligence in Urologic Documentation: A Review of Emerging Capabilities and the Ongoing Need for Human Oversight.

PURPOSE OF REVIEW: Clinical documentation continues to expand in volume and complexity, spanning outpatient encounters, inpatient summaries, patient-p...

Data-driven outcome prediction and rational resource allocation in severe traumatic brain injury: a multicenter retrospective study integrating survival analysis and machine learning ensembles.

INTRODUCTION: Severe traumatic brain injury (sTBI), is a leading cause of death and disability among young and middle-aged populations worldwide. OBJE...