Infection Control

Key factors of the deranged antiviral response in elderly patients with COVID-19: a machine-learning analysis.

Age is a well-known risk factor to develop severe viral respiratory infections, including severe COVID-19. This study aimed to identify the biological alterations linked to severe disease in elderly patients with COVID-19. For this purpose, we employed a derivation cohort with 450 SARS-CoV-2 infected and unvaccinated patients admitted to hospital wards and a validation cohort with 244 SARS-CoV-2 i...

Generative artificial intelligence for surgical site infection surveillance.

BACKGROUND: Surgical site infection (SSI) surveillance can be time consuming and resource intensive. This study investigates the potential of generative artificial intelligence (GenAI) to augment the detection and classification of SSIs. METHODS: A case control study of patients with SSI following spine surgery at one US hospital. SSIs were classified into superficial, deep, and organ space. All S...

An AI framework for automated quality control of paraffin block and slide consistency: a clinical evaluation and human-machine comparison study.

Consistency between paraffin blocks and corresponding histological slides is a key component of pathological quality control. In routine practice, ver...

Comorbidity Burden and Length of Stay After Myocardial Infarction: A Retrospective Study Using Large Language Model-Assisted Chart Abstraction in a Tertiary Cardiac Hospital.

Patients' length of stay (LOS) during admission for myocardial infarction (MI) represents a closely tracked outcome metric for Cardiology services, wh...

Cross-sectional research: Application of an Artificial Intelligence-Based Pediatric Early Warning Score in the Pediatric Emergency Department.

BACKGROUND: There are a large number of pediatric emergency patients. Due to the fact that the children cannot describe their own conditions, there is...

Construction and interpretability evaluation of a prediction model for radiographic pneumonia in children at outpatient and emergency departments.

BACKGROUND: Radiographic confirmation is crucial for pediatric pneumonia diagnosis, but chest X-ray overuse in outpatient and emergency settings raise...

[Comparative observation of analgesic efficacy between liposomal bupivacaine and "cocktail" therapy following artificial intelligence-assisted direct anterior approach total hip arthroplasty: A prospective randomized controlled study].

OBJECTIVE: To compare the analgesic efficacy and safety of liposomal bupivacaine (LB) versus ropivacaine for surgical incision local anesthesia after ...

Predicting Nosocomial Infections in Hematologic Patients: A Machine Learning Model Based on Dynamic Body Temperature Trajectories.

AIMS: To identify body temperature dynamic patterns and develop a machine learning model for the early detection of nosocomial infections. DESIGN: A r...

Responsible AI for Predicting Delayed Hospital Discharge Among Older Adults: Development and Evaluation Study for Balancing Accuracy, Equity, and Explainability.

BACKGROUND: Amid growing demands and constrained health care resources, effective hospital bed capacity management is crucial. Delayed hospital discha...

Digital Monitoring of Pre-Exposure Prophylaxis Users Through Electronic Patient-Reported Outcome Measures and Electronic Patient-Reported Experience Measures: Multicenter Prospective Study on Feasibility, Safety, and Predictive Modeling of Digital Engagement.

BACKGROUND: Digital health tools integrating electronic patient-reported outcome and experience measures (ePROMs/ePREMs) enable longitudinal monitorin...

Performance of Machine Learning Models for Sepsis and Stroke Detection Using EMS Data.

OBJECTIVES: Early sepsis and stroke recognition by emergency medical services (EMS) improves triage, treatment, and patient outcomes. Machine learning...

Using Machine Learning to Improve Screening for Oropharyngeal Dysphagia in Hospitalized Versus Primary Care Adult Patients With COVID-19 Disease: Retrospective Observational Study.

BACKGROUND: Oropharyngeal dysphagia (OD) commonly occurs in patients with COVID-19 disease, posing diagnostic challenges due to isolation protocols. O...

[Expert consensus on optimizing the multidisciplinary clinical pathways and management models for pulmonary function testing].

The promotion and application of pulmonary function tests (PFTs) in China have achieved preliminary success;however, numerous deficiencies persist in ...

A multiparameter model (OsteoSC-M3) for early detection and risk stratification of osteoporosis in women: a multicentre cohort study in China.

BACKGROUND: Osteoporosis is a major global health issue, but current early screening tools lack accuracy, and the gold-standard diagnostic method, dua...

Prediction of unplanned readmission in older adults during hospital stay: a data-driven approach to support care transition.

PURPOSE/AIMS: Accurately predicting 30-day unplanned readmission in older adults is critical for improving care transitions and reducing preventable h...

Facilitators and barriers of research engagement in a large teaching hospital in the Netherlands: a narrative reflection.

BACKGROUND: Healthcare organisations are facing major challenges, including workforce shortages, rising costs, and an aging population. Research engag...

Effect of a mobile health intervention optimised with artificial intelligence on blood pressure and other cardiovascular risk factors in adults with high blood pressure: rationale and design of My Intelligent Cardiac Assistant (MICArdiac) randomised controlled trial.

INTRODUCTION: Control of blood pressure (BP) continues to be a challenge globally. Clinical trials have shown home BP monitoring and text-message inte...

Exploring novel kinetics of automated H2O2 nebulization: a breakthrough in SARS-CoV-2 elimination.

Although hydrogen peroxide (H2O2) nebulization has shown promise for reducing SARS-CoV-2 loads in healthcare settings, its precise kinetics and real-w...

Synthetic data-augmented machine learning for 30-day readmission prediction in patients with chronic conditions: a retrospective real-world study.

OBJECTIVES: To develop and evaluate an explainable machine learning framework enhanced with synthetic data generation to predict unplanned 30-day hosp...

Predictive Value of Machine Learning for Poststroke Mortality Risk: Systematic Review and Meta-Analysis.

BACKGROUND: People with stroke face a high mortality risk, and an accurate prediction model is essential to the guidance of clinical decision-making i...