Anesthesiology

Development, internal testing, and external validation of an interpretable machine-learning model for predicting imaging-confirmed in-hospital postoperative deep vein thrombosis in older patients with patellar fractures.

BACKGROUND: Older patients with patellar fractures may be at increased risk of postoperative deep vein thrombosis (DVT) because of trauma, perioperative immobilization, and age-related prothrombotic susceptibility. However, risk-stratification tools tailored to this specific population remain limited. We aimed to develop, internally test, and externally validate an interpretable machine-learning m...

Artificial intelligence in pediatric pain: a systematic review.

BACKGROUND: Pain is a challenging, multifaceted symptom reported by most pediatric patients. This systematic review aims to explore the progress and effectiveness of applying artificial intelligence (AI) technology in pediatric pain management. METHODS: A comprehensive search of PubMed, Embase, Web of Science, Cochrane, Scopus, IEEE Xplore, ACM Library, and ClinicalTrials.gov was conducted. The se...

Substance-induced manic psychosis in which delusions were corroborated by a chatbot - case report.

BACKGROUND: This case describes a substance-induced manic episode with psychotic features in which interaction with an AI (artificial intelligence) ch...

Operational Integration and Temporal Validation of a Continuously Deployed ICU Prediction Model.

OBJECTIVES: To operationalize and temporally validate an electronic medical record (EMR)-integrated machine learning system (Big data-driven Evaluatio...

Impact of Deep-Learning Reconstruction on MRI Workflows: A Retrospective Analysis at a Large Academic Tertiary Center.

PURPOSE: Artificial intelligence is increasingly integrated in clinical practice. In radiological imaging, deep-learning (DL)-based image reconstructi...

Bioactive compounds for neuroinflammation and neuropathic pain management: molecular and cellular mechanisms.

Bioactive compounds are a promising multi-target strategy for managing neuroinflammation and chronic pain. Bioactive compounds such as Paeonol, Kaempf...

A two-step deep learning framework for predicting difficult video laryngoscopy from ultrasound images: a prospective cohort study.

BACKGROUND: Deep learning integrated with ultrasound systems may assist in predicting difficult airway, a life-threatening complication in anesthesia....

Identification of Pathological Secretions in Bronchoscopic Images Based on Edge Features and Multi-Scale Attention Mechanism.

The accumulation of pathological bronchial secretions compromises ventilation and oxygenation in critically ill patients and may lead to atelectasis o...

A Hierarchical Multimodal Framework for Sedation Monitoring in ICU Patients.

In the intensive care unit (ICU), monitoring sedation levels is crucial. Clinicians often rely on intermittent behavioral scales like the Richmond Agi...

Clinical subtypes and prognosis of new-onset atrial fibrillation in critically ill patients.

BACKGROUND: New-onset atrial fibrillation (NOAF) is a common cardiovascular complication in critically ill patients and is consistently associated wit...

EEG monitoring in the operating room: current uses and perspectives - a narrative review.

CONTEXT AND IMPORTANCE: With over 300 million surgeries performed under general anaesthesia annually, optimising perioperative brain health has become...

Machine learning prediction of long-term postoperative pneumonia risk: a retrospective cohort study.

BACKGROUND: Postoperative pneumonia is a significant complication, highlighting a patient's ongoing vulnerability. While traditional tools focus on sh...

Machine Learning-Based Prediction of Treatment Success, Postoperative Pain, and Analgesic Use After Full Pulpotomy in Permanent Molars with Symptomatic Irreversible Pulpitis.

INTRODUCTION: This study aimed to develop and evaluate machine learning (ML) models for predicting treatment success, postoperative pain, and analgesi...

Predict neuromuscular performance in human epidural electrical stimulation: phase 1 trial interim results.

BACKGROUND: Epidural electrical stimulation (EES) has emerged as a promising therapy for restoring motor function in patients with paralysis. A primar...

Integrating multidimensional nociceptive-related cortical features for unsupervised assessment of anesthesia states in rats.

Accurate anesthesia monitoring remains challenging because current approaches primarily assess consciousness while overlooking nociceptive processing....

Artificial intelligence in emergency mechanical ventilation: a prospective observational comparison with emergency physician ventilator settings.

BACKGROUND: Artificial intelligence (AI) has the potential to support clinicians in high-risk and complex decision-making processes, such as mechanica...

Evaluation of the accuracy, quality, and readability of large language models on local anesthesia and general anesthesia-sedation in dentistry.

PURPOSE: This study aims to compare the responses provided by commonly used artificial intelligence-based chatbots such as ChatGPT-3.5, ChatGPT-4o, Ge...

Development and Validation of an Integrated Artificial Intelligence-Powered Clinical Decision Support Application for Cardiac Critical Care: Combining Coagulation Management, Blood Gas Analysis, Mechanical Ventilation, Hemodynamic Assessment, and Extracorporeal Membrane Oxygenation.

This study describes the development and preliminary validation of an integrated clinical decision support application (Cardiac Critical Care Advisor ...

Caudal Anesthesia Patient Education Materials: Comprehensive Analysis of Generative Artificial Intelligence and Traditional Patient Information Leaflets.

Artificial intelligence models for predicting ASA physical status classification: a systematic review and meta-analysis.

BACKGROUND: The American Society of Anesthesiologists (ASA) physical status classification remains the cornerstone of preoperative risk assessment but...