Infection Control

Beyond episodic early warning systems: a continuous clinical alert system for early detection of in-hospital deterioration.

Efficient patient monitoring on the medical-surgical wards is crucial to prevent significant in-hosp...

The role of phenotypic age acceleration in aneurysmal subarachnoid hemorrhage: analysis of retrospective data from two hospital-based cohorts and prospective UK Biobank cohort.

BACKGROUND: Phenotypic age acceleration (PhenoAgeAccel) is considered a major risk factor for variou...

Prediction model of in-hospital mortality risk in intensive care unit patients with cardiac arrest: a multicenter retrospective cohort study based on an ensemble model.

BACKGROUND: In-hospital cardiac arrest (IHCA) is a major adverse event with a high death risk. Machi...

A Prospective Comparative Study of the Effectiveness of Flap Fixation by Suture Versus Conventional Closure in Reducing Seroma Formation After Modified Radical Mastectomy.

Background Seroma formation is a common postoperative complication of modified radical mastectomy (M...

Detection of ESBL-producing complex with VITEK 2 system and screening cutoffs for implementing confirmatory tests.

complex (C) are important nosocomial pathogens that can be reservoirs of transmissible extended-spe...

Anomaly Detection in Electronic Health Records Across Hospital Networks: Integrating Machine Learning With Graph Algorithms.

In a large hospital system, a network of hospitals relies on electronic health records (EHRs) to mak...

Point-counterpoint: What is the best strategy for developing generative AI for hospital medicine?

Generative Artificial Intelligence (Gen AI) shows significant promise as a technology that could imp...

Exploring Suitability of Low-Severity Rating Hospital Incident Reports for Machine Learning.

Electronic incident reporting is a key quality and a safety process for healthcare organizations tha...

Perception and Knowledge of Hospital Workers Toward Using Artificial Intelligence: A Descriptive Study.

OBJECTIVE: This study aims to assess the perception and knowledge of hospital workers toward using a...

Predicting 30-day survival after in-hospital cardiac arrest: a nationwide cohort study using machine learning and SHAP analysis.

OBJECTIVE: In-hospital cardiac arrest (IHCA) presents a critical challenge with low survival rates a...

Machine learning approach for optimizing usability of healthcare websites.

In today's digital era, hospital websites serve as crucial informational resources, providing patien...

Effect of AI-based pre-hospital health education via QR code on APAIS scores in patients with breast nodules: A retrospective study.

PURPOSE: To explore the effect of AI-based pre-hospital health education via QR code on preoperative...

Development of explainable artificial intelligence based machine learning model for predicting 30-day hospital readmission after renal transplantation.

BACKGROUND: Hospital readmission following renal transplantation significantly impacts patient outco...

Predicting mortality and risk factors of sepsis related ARDS using machine learning models.

Sepsis related acute respiratory distress syndrome (ARDS) is a common and serious disease in clinic....

Unraveling relevant cross-waves pattern drifts in patient-hospital risk factors among hospitalized COVID-19 patients using explainable machine learning methods.

BACKGROUND: Several studies explored factors related to adverse clinical outcomes among COVID-19 pat...

Machine learning for high-risk hospitalization prediction in outpatient individuals with diabetes at a tertiary hospital.

OBJECTIVE: To characterize, via a predictive model using real-world data, patients with diabetes wit...

Utilizing machine learning and geographic analysis to improve Post-crash traffic injury management and emergency response systems.

Traffic injuries are a major public health concern globally. This study uses machine learning (ML) a...

Gender Disparities in Artificial Intelligence-Generated Images of Hospital Leadership in the United States.

OBJECTIVE: To evaluate demographic representation in artificial intelligence (AI)-generated images o...

Predicting hospital admissions, ICU utilization, and prolonged length of stay among febrile pediatric emergency department patients using incomplete and imbalanced electronic health record (EHR) data strategies.

OBJECTIVE: Determine the efficacy of commonly used approaches to handling missing and/or imbalanced ...

Comment on "Machine learning risk-prediction model for in-hospital mortality in Takotsubo cardiomyopathy".

Real-time surveillance system for patient deterioration: a pragmatic cluster-randomized controlled trial.

The COmmunicating Narrative Concerns Entered by RNs (CONCERN) early warning system (EWS) uses real-t...