Infection Control

Enhancing hospital workforce planning, scheduling, and performance evaluation through an AI-driven human resource management system.

Efficient workforce management is critical for ensuring the quality, safety, and sustainability of hospital operations. Traditional human resource management (HRM) approaches often rely on manual processes that are prone to errors, lack adaptability, and fail to adequately balance staff preferences with patient care requirements. To address these challenges, this research proposes an AI-driven HRM...

Accurate, fair, and generalisable scaling of injury severity score-based AI with demographics in terms of mortality in patients with trauma: multi-centre, multi-national retrospective cohort study.

BACKGROUND: Accurate and equitable prediction of trauma-related in-hospital mortality is critical for guiding clinical decisions and optimising trauma care resources. Traditional severity scoring systems like the Injury Severity Score (ISS) do not account for demographic factors, potentially limiting their fairness and generalisability across diverse populations. METHODS: We developed and external...

A scalable framework for population-level precision health: Insights from sleep disorders.

Assessing population-level risk patterns of sleep disorders is challenging. Many studies rely on hospital-based samples, which can be biased toward in...

AI-powered Chatbot integration for enhanced accessibility of electronic health records in a pediatric hospital.

Navigating electronic health records (EHRs) remains a time-consuming task for clinicians, especially in resource-constrained healthcare settings. This...

Investigating the Effect of Hospital Infection Control Informatization on Optimizing Microbiological Specimen Submission Before Antibiotic Therapy: Failure Mode and Effects Analysis.

BACKGROUND: Antimicrobial resistance (AMR) poses a critical global health threat, with inappropriate antibiotic use being a major driver. Timely micro...

Enhanced Prediction of Atrial Fibrillation in Patients With Ischemic Stroke Through Electronic Medical Records and Text Mining: Algorithm Development and Validation.

BACKGROUND: Stroke remains one of the leading causes of mortality and long-term disability worldwide. Atrial fibrillation (AF) is a major and often un...

Telepathology and Mobile Health System for Province-Wide Pathology Consultation in Henan, China: Retrospective Evaluation Study.

BACKGROUND: Telepathology has emerged as a transformative digital health solution to address the global shortage of pathologists and the unequal distr...

[Deep learning-based assessment of periodontal ligament area changes in maxillary central incisors under different orthodontic regimens using cone-beam CT images].

Objective: To investigate the differences in the changes of periodontal ligament area (PDLA) and related clinical indicators before and after maxillar...

Predictive accuracy of Early Warning Score Systems for Detecting Critically Ill Patients in an Outpatient Setting.

Background No systematic methods exist for triaging outpatients with severe conditions. Our previous pilot study suggested that the National Early War...

In-Hospital Mortality Prediction of Patients Requiring Extracorporeal Membrane Oxygenation Using Composite Lactate Metrics and Weight of Evidence Modeling.

BACKGROUND: Mortality prognostication in adult patients requiring extracorporeal membrane oxygenation (ECMO) is not accurate or established. We hypoth...

Machine Learning for Estimating Cardiorespiratory Fitness in Patients With Obesity: Protocol for a Retrospective and Prospective Multicenter Cohort Study.

BACKGROUND: Cardiorespiratory fitness (CRF) is a key predictor of cardiovascular and other health-related diseases in individuals with obesity. CRF is...

Artificial Intelligence Length-of-Stay Forecasting and Pediatric Surgical Capacity.

IMPORTANCE: Hospitals are increasingly experiencing challenges with variable and unpredictable inpatient loads, including days with excessively high a...

A fine-grained transformer combined with multimodal data for predicting hospital length of stay in acute coronary syndrome.

The prediction of hospital length of stay (LOS) is of great significance for hospitals to rationally allocate medical resources and provide timely tre...

NLP in Support of Pharmacovigilance: QUality Adverse Drug Reaction AcTIve Control (QUADRATIC).

Adverse drug reactions (ADRs) are a major cause of morbidity, hospital admissions, and in-hospital mortality, yet remain incompletely captured by post...

Incisional hernia prediction using machine learning models.

BACKGROUND: One of the main complications after laparotomy is incisional hernia (IH), with an incidence of 40% in specific risk groups. There is no co...

Predicting Nocturnal Hypertension in CKD Through Table-Value Diffusion Model.

BACKGROUND: Ambulatory blood pressure monitoring is indispensable for diagnosing nocturnal hypertension (NH) among patients with chronic kidney diseas...

Impact of GPT-4-Generated Discharge Letters on Patients' Medical Comprehension: Prospective Crossover Study.

BACKGROUND: Patients often struggle to understand standard hospital discharge letters, increasing the risk of medication errors and misunderstandings....

An integrated random forest- and LASSO-derived nomogram for predicting postoperative nosocomial infections in colorectal cancer patients.

Interpretable machine learning for chronic kidney disease prediction: Insights from SHAP and LIME analyses.

Chronic kidney disease (CKD) is a progressive condition requiring early detection for optimal patient outcomes. This study developed an interpretable ...

Comprehensive assessment of postoperative metachronous liver metastasis risk in colon cancer based on inflammatory indicators: a multicenter prospective study.

OBJECTIVE: Insidiousness is a hallmark of metachronous liver metastasis. Owing to the absence of a comprehensive machine-learning model integrating sy...