Anesthesiology

Joint-specific measures improve risk adjustment in total knee arthroplasty: A machine learning approach.

PURPOSE: Accurate risk adjustment in total knee arthroplasty (TKA) is essential for outcome prediction and quality assessment. Most existing prediction models rely solely on patient demographics and comorbidities and do not account for joint-specific pathology. This study evaluated whether incorporating radiographic and clinical joint-specific parameters improves machine learning (ML)-based risk a...

A New Study Partner: Leveraging Artificial Intelligence for the Anesthesiology APPLIED Exam.

DMRNet: a dynamic multi-scale residual network for Shamrock view and lumbar plexus segmentation.

Lumbar plexus block (LPB) is a regional anesthesia technique widely used for hip and knee surgeries. However, despite the assistance of ultrasound gui...

Interpretable machine learning models for predicting perioperative myocardial injury in non-cardiac surgery.

AIMS: Perioperative myocardial injury (PMI) is a frequent and often asymptomatic complication after non-cardiac surgery and is associated with increas...

Nationwide 30-Day Surgical Outcomes in Korea: An Interim Analysis of the Korean Quality Improvement Platform in Surgery.

BACKGROUND: National surgical registries such as the American College of Surgeons NSQIP and Japan's National Clinical Database have shown that structu...

Initial assessment of suspected cervical spine fracture in the emergency department: A contemporary narrative review.

Cervical spine fractures represent a potentially catastrophic consequence of blunt trauma. Early identification of unstable injuries is critical to pr...

Integrating artificial intelligence into paediatric interventional radiology: a review of emerging applications and future directions.

Artificial intelligence (AI) is heralded to revolutionise healthcare by improving efficiency, personalising care, and enhancing clinical outcomes. Alt...

TRPV1, Endocannabinoid, and Opioid Systems in Analgesia: Molecular Mechanisms and Drug Development Strategies.

Pain modulation relies on complex molecular interactions among ion channels, G protein-coupled receptors, and intracellular signaling cascades. The Tr...

Multimodal assessment of minimally conscious state and cognitive motor dissociation in neurocritical care: A critical review.

Minimally conscious state (MCS) is characterized by inconsistent but clearly discernible clinical and behavioral evidence of consciousness. Cognitive ...

Advances in Ultrasound-Guided Fascial Plane Blocks for Perioperative Acute Pain Management.

INTRODUCTION: Perioperative acute pain remains a major challenge because conventional analgesic strategies are often limited by inadequate efficacy an...

Preoperative risk assessment for surgical operations using artificial intelligence: Potential benefits, hurdles, and future directions.

Artificial intelligence offers the potential of examining large clinical data sets to uncover complex nonlinearities and personalized associations whe...

The role of emerging technology in expanding regional anesthesia education and patient access.

PURPOSE OF REVIEW: The purpose of this article is to identify promising technologies that can enhance core regional anesthesia training, competence, a...

Large Language Models vs. Machine Learning on Structured Perioperative Data: Does Model Choice Matter?

The study by Ko and colleagues provides evidence that large language models may achieve modestly improved performance compared with traditional machin...

Acute brain dysfunction clusters in COVID-19: a pilot machine learning-based analysis of the COVID-D cohort.

PURPOSE: While acute brain dysfunction (ABD, i.e., delirium and coma) is associated with significantly increased morbidity in critically ill patients,...

Supervised Fine-Tuning of Large Language Models With Chain-of-Thought Reasoning for Pediatric Heart Disease Detection in Unstructured Echocardiogram Reports: Algorithm Development and Validation.

BACKGROUND: Pediatric heart disease (PHD), including congenital heart defects, is often incompletely captured in electronic health records, particular...

Operator wellbeing as a translational endpoint: a dimension missing from the AI implementation framework in anesthesiology.

Association of Staphylococcus aureus bloodstream infection with 7-day incident delirium in critically Ill adults: a propensity-weighted competing risk analysis.

BACKGROUND: Delirium is a frequent manifestation of acute brain dysfunction in critically ill patients with bloodstream infections (BSI). While the as...

Explainable AI reveals squamous histology and U-shaped PD-L1 patterns as primary subgroup predictors of neoadjuvant and perioperative immunotherapy benefit in NSCLC: a machine learning analysis.

BACKGROUND: The introduction of neoadjuvant and perioperative immunotherapy has broadened treatment options for resectable non-small cell lung cancer ...

Recommendations for disclosure of artificial intelligence in scientific writing and publishing: a regional anesthesia and pain medicine modified Delphi study.

INTRODUCTION: The use of artificial intelligence (AI) in the scientific process is advancing at a remarkable speed, thanks to continued innovations in...

Raw EEG as a viable alternative to engineered decompositions in anesthetic depth prediction.

PURPOSE: Assessing the depth of anesthesia remains a challenge in operating rooms worldwide, as hospitals often rely on proprietary monitors that are ...