Hospital-Based Medicine

Artificial Intelligence in Trauma Care: A Systematic Review of Resuscitation, Diagnosis, Risk Prediction, and Management.

BACKGROUND: Artificial intelligence (AI) is increasingly being explored in trauma care as a tool to support clinical decision-making. OBJECTIVE: To evaluate current evidence on AI applications in trauma resuscitation, diagnosis, complication prediction, and patient management. METHODS: A systematic review was conducted using PubMed, Web of Science, ScienceDirect, and Cochrane databases to identify...

Explainable transfer learning ensemble AI model for lung ultrasound pneumothorax detection with expert benchmark.

BACKGROUND: Lung ultrasound is essential for rapid, radiation-free bedside pneumothorax diagnosis but limited by variability in human interpretation. Key gaps include insufficiently large and diverse human datasets, inconsistent image acquisition, lack of rigorous expert benchmarking, and inadequate clinical interpretability of existing artificial intelligence models. We aimed to develop and valid...

Comparing regular expression and machine learning approaches to predict immigrant status from primary care electronic medical record data in Ontario, Canada.

New immigrants often face barriers when navigating the healthcare system, which can create unmet healthcare needs and contribute to health inequities....

Evidence-based action plan for integrating artificial intelligence in an academic medical centre-a multidisciplinary approach.

INTRODUCTION: As the effectiveness of artificial intelligence (AI) in enhancing various facets of healthcare delivery becomes more apparent, it is ant...

IFCN position statement: use of artificial intelligence in clinical neurophysiology.

In recent years, artificial intelligence (AI) has made significant strides, gaining traction across various domains, including clinical medicine. The ...

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...

Changes in computed tomography derived muscle and pulmonary tissue in patients hospitalized for COVID-19: a 12-month follow-up study.

BACKGROUND: Prolonged muscle loss and persistent pulmonary radiological manifestations have been observed among previously hospitalized COVID-19 patie...

Explainable machine learning for predicting infections that require hospitalization in patients with systemic lupus erythematosus.

OBJECTIVES: To develop and validate an explainable artificial intelligence (XAI)-based machine learning (ML) model for predicting infections requiring...

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...

Association of initial core volume on non-contrast CT using a deep learning algorithm with clinical outcomes in acute ischemic stroke: a potential tool for selection and prognosis?

BACKGROUND: In an extended time window, contrast-based neuroimaging is valuable for treatment selection or prognosis in patients with stroke undergoin...

Artificial Intelligence in Haemophilia Care: A Narrative Review of Current Evidence and Future Opportunities.

Artificial intelligence (AI) is increasingly explored in healthcare for its capacity to analyse complex data, support clinical decision-making and ena...

Seasonal variations in sources and dynamics of surface water-groundwater nitrate in a plain river network area: Based on hydrochemical, dual isotope approach and feature importance interpretation.

Understanding the seasonal dynamics of nitrate pollution in interconnected surface water (SW) and groundwater (GW) systems is critical for effective n...

Ethical Considerations for Artificial Intelligence Tools in Small Animal Veterinary Medicine.

As veterinary artificial intelligence (AI) tools become more available, it is vital to ensure that they genuinely promote patient well-being and avoid...

Implementation and User Evaluation of an On-Premise Large Language Model in a German University Hospital Setting: Cross-Sectional Survey.

BACKGROUND: Large language models (LLMs) are increasingly used by employees at university hospitals for information retrieval or decision support. Sel...

Multidisciplinary blinded randomized expert evaluation of large language models for clinical diagnosis and management.

BACKGROUND: Direct clinical uses of large language models (LLMs) remain controversial, partly because of the lack of methodological rigor in assessing...

[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 ...

Risk-Guided Atrial Fibrillation Screening With Artificial Intelligence-Enabled Electrocardiogram Models: A VITAL-AF Trial Analysis.

BACKGROUND: Screening for atrial fibrillation (AF) may lead to earlier detection and initiation of preventive measures. Current AF screening approache...

Contextualizing the Patient Blood Management (PBM) Program Through the Lens of Bioethical Principles.

In an increasingly specialized medical landscape, Patient Blood Management (PBM) has emerged as a multidisciplinary and ethically grounded approach to...

Nurses' Evaluation of a Service Robot for Inpatient Care: Technology Acceptance Study.

BACKGROUND: The integration of robotic systems into nursing practice is increasingly discussed as a potential strategy to alleviate workload and suppo...

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...