Infection Control

Prioritising Hospital Complaints: An Innovative Tool Using Large Language Model-Assisted Content Analysis and Machine Learning Algorithms

In clinical settings, patients often express dissatisfaction through narrative speech or written text. However, most complaints management systems still rely on manual review or rulebased methods that fail to capture the severity or urgency of complaints. This leads to inconsistent triage, delayed resolution and missed opportunities for systemic improvement. A novel model leveraging large language...

Early Warning Model for Patient Deterioration: A Machine Learning Approach for Nurse-Led Monitoring

The early recognition of clinical deterioration in hospital inpatients continues to be a major challenge in healthcare. In this work, we proposed an intelligible machine learning (iML) based EWS for predicting patient deterioration events and facilitating early nurse interventions. We compare a range of supervised learning models, including gradient boosting and logistic regression on electronic h...

A Hybrid AutoML Ensemble Integrating Conventional Learners and Gradient-Boosting Models for Multi-Outcome Prediction in ICU Patients with Pseudomonas aeruginosa

Carbapenem resistance in Pseudomonas aeruginosa is increasing in intensive care units (ICUs). To enhance antimicrobial stewardship and infection contr...

CLIF-Net: Intersection-guided Cross-view Fusion Network for Infection Detection from Cranial Ultrasound

This paper addresses the problem of detecting possible serious bacterial infection (pSBI) of infancy, i.e. a clinical presentation consistent with bac...

Case-Control Matching Erodes Feature Discriminability for AI-driven Sepsis Prediction in ICUs: A Retrospective Cohort Study

Sepsis remains a leading cause of intensive care unit (ICU) mortality worldwide, and early detection is essential for improving survival through timel...

Advancing In-Hospital Mortality Prediction for Acute Myocardial Infarction: an analysis from the American Heart Association Get-With-the-Guidelines Coronary Artery Disease Registry

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, with acute myocardial infarction (AMI) contributing to over 100,000 dea...

Privacy Protection for Chinese Electronic Medical Records Using Large Language Models: Effectiveness Evaluation and Application of LLM Models in Medical Data Tasks

The privacy protection of medical patients has remained a critical concern in healthcare information management during the digital era. Conventional a...

AI-generated patient-friendly discharge summaries to empower patients

Patients often struggle to fully understand their discharge letters after inpatient hospital stays, which are often replete with domain-specific medic...

Portability of an artificial intelligence model for self-harm detection across hospital settings

Adequate self-harm surveillance is a key part of suicide prevention efforts. Our prior work has demonstrated the efficacy of an artificial intelligenc...

Development and Validation of VC-MAES and VC-SEPS: Deep Learning-Based Early Warning Systems for Hospitalized Patients

The timely detection of ward deterioration—including unplanned intensive care unit (ICU) transfer, cardiac arrest, death, and sepsis—remains an unmet ...

Automated Deep Learning Pipeline for Callosal Angle Quantification

Normal pressure hydrocephalus (NPH) is a potentially treatable neurodegenerative disorder that remains underdiagnosed due to its clinical overlap with...

Diagnostic Codes in AI prediction models and Label Leakage of Same-admission Clinical Outcomes

Artificial intelligence (AI) and statistical models designed to predict same-admission outcomes for hospitalized patients, such inpatient mortality, o...

Predicting Hospital Admissions Using Pretrained EHR Embeddings: External Evaluation and Insights on Local Vocabulary Adaptation

Unplanned hospital admissions impose substantial strain on healthcare systems, yet predictive models for these events remain underexplored in practice...

From Clinical Judgment to Large Language Models: Benchmarking Predictive Approaches for Unplanned Hospital Admissions

While machine learning (ML) models show strong performance for predicting unplanned hospital visits, their clinical utility relative to physician judg...

Harnessing Machine Learning for Antimicrobial Resistance Surveillance in Zimbabwe

Antimicrobial resistance (AMR) poses a significant public health challenge, particularly in resource-limited settings such as Zimbabwe, where surveill...

Explainable Artificial Intelligence for Prognostic Stratification in Out-of-Hospital Cardiac Arrest Patients Undergoing Extracorporeal Cardiopulmonary Resuscitation

Prognostication in patient with out-of-hospital cardiac arrest (OHCA) underwent extracorporeal cardiopulmonary resuscitation (ECPR) remains challengin...

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

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

Towards Automated Neonatal EEG Analysis: Multi-Center Validation of a Reliable Deep Learning Pipeline

To evaluate the reliability and generalization of NeoNaid, a fully automated software tool for neonatal EEG analysis, based on functional brain age (F...

Effect and Mechanisms of a Voice-based Coach using AI on Psychological Distress: A Phase 2 Randomized Trial

Artificial Intelligence (AI) voice applications have the potential to address the unmet treatment needs among patients with depression and anxiety, bu...

Understanding Uncertainty in Large Language Model Predictions of Early Death in Critically Ill Patients: A Conformal Prediction Approach

Early prediction of in-hospital death remains a significant challenge due to the limited availability of structured data during initial admission. Uns...