Anesthesiology

AnesNet: a versatile deep convolutional framework for predicting depth of anesthesia using BIS and multimodal intraoperative signals.

Neoadjuvant Radiation is Causally Linked to Increased Operative Time and Perioperative Blood Transfusion in Pancreatic Ductal Adenocarcinoma.

INTRODUCTION: Blood transfusion in patients undergoing surgical resection for pancreatic ductal adenocarcinoma (PDAC) is associated with worse outcomes. As the treatment paradigm shifts toward neoadjuvant therapy, little is known about how this may influence perioperative blood transfusion. MATERIALS AND METHODS: The American College of Surgeons National Surgical Quality Improvement Program (ACS-N...

Generative AI in preanesthetic consultations: Effects on efficiency, documentation workload, quality, and physician-patient interaction: A simulation trial.

BACKGROUND: Clinicians spend over 30% of their workday on electronic health records, reducing patient interaction and contributing to burnout. Preanes...

Strategies to reduce perioperative acute kidney injury in non-cardiac adult surgeries: the secret sauce.

Acute kidney injury is a common perioperative complication that leads to significant downstream effects on the patient and the health system. Patients...

Ultra-Fast Sub-Minute Brain MRI with Deep-Learning-reconstruction for Anesthesia-Free Emergency Imaging in Children.

PURPOSE: As MRI frequently requires general anesthesia in pediatric patients, there is an undersupply in clinical routine. This may result in delayed ...

Sustainable Ophthalmology Applications: From the Perspective of Strabismus and Pediatric Ophthalmology.

Ophthalmology significantly contributes to the healthcare sector's carbon footprint. Despite recent increases in sustainability research in ophthalmol...

Fine-Tuned Large Language Models for Generating Multiple-Choice Questions in Anesthesiology: Psychometric Comparison With Faculty-Written Items.

BACKGROUND: Multiple-choice examinations (MCQs) are widely used in medical education to ensure standardized and objective assessment. Developing high-...

Insights on Recruitment, Implementation, and Movement Pattern Detection by Exploring the Feasibility of Sensor-Based Insole Technology in Long-Term Care: Mixed Methods Feasibility Study.

BACKGROUND: Sensor-based footwear is increasingly discussed as a promising tool for mobility monitoring and fall-risk assessment, yet its applicabilit...

Assessing the Role of Large Language Models in Veterinary Dentistry Client Communication.

This study evaluated the accuracy, consistency, and clinical appropriateness of responses generated by large language models (LLMs) to frequently aske...

An ultrasound-based artificial intelligence framework for difficult airway prediction: A two-model, three-step decision framework.

BACKGROUND: At present, the early warning of difficult airway remains fraught with challenges. Previous ultrasonic quantitative parameters have demons...

Justifying model complexity: Evaluating transfer learning against classical models for intraoperative nociception monitoring under anesthesia.

BACKGROUND: Accurate intraoperative detection of nociceptive events is essential for optimizing analgesic administration and improving postoperative o...

Automated Segmentation of Stellate Ganglion Block Region in Ultrasound Images Using Deep Learning Model.

BACKGROUND: The stellate ganglion region is densely vascularized and innervated, making the stellate ganglion block (SGB) technically challenging unde...

A deep learning model integrating structured data and clinical text for predicting atrial fibrillation recurrence.

Multimodal perioperative data from patients undergoing atrial fibrillation (AF) ablation offer valuable insights for stratifying recurrence risk, yet ...

Essential Updates 2024-2025: Surgical Strategy for Esophageal Cancer Toward a New Paradigm in the Era of Immunotherapy and Personalization.

Esophageal cancer surgery is evolving from technical standardization to a paradigm of personalized, strategy-oriented care. Robotic-assisted technique...

Artificial intelligence for surgical care in war-torn sudan: Feasibility, barriers, and ethical perspectives from a conflict zone.

BACKGROUND: Artificial intelligence (AI) offers transformative potential for clinical care, yet its deployment in conflict-affected, low-resource sett...

Development and external validation of a machine learning model for predicting in-hospital mortality in acute liver failure.

BACKGROUND: Acute liver failure (ALF) is a rapidly progressive and life-threatening condition that requires accurate risk stratification. Existing pro...

Artificial Intelligence-Assisted Point-of-Care Ultrasound for Evaluating Left Ventricular Ejection Fraction: A Systematic Review of Prospective Observational Studies.

Artificial intelligence (AI) embedded in point-of-care ultrasound (POCUS) could reduce operator dependence in left ventricular ejection fraction (LVEF...

Artificial intelligence-enhanced ECG score for perioperative risk assessment in non-cardiac surgery.

AIMS: The role of electrocardiography (ECG) has been limited in the preoperative risk evaluation in noncardiac surgery due to its low prognostic value...

Artificial intelligence and predictive analytics in obstetric anesthesia: early warning for maternal complications.

PURPOSE OF REVIEW: Maternal morbidity and mortality remain largely preventable, yet current risk-assessment tools identify only a fraction of women wh...

Size doesn't matter: Assessing the trustworthiness of large language models in medical contexts: A focus on epidural information retrieval.

BACKGROUND: Since the release of ChatGPT, numerous LLMs have emerged, providing easy access to information without the need for technical expertise. H...