AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Emergence Delirium

Showing 1 to 7 of 7 articles

Clear Filters

Effects of nefopam on emergence agitation after general anesthesia for nasal surgery: A prospective, randomized, and controlled trial.

Medicine
BACKGROUND: Emergence agitation (EA) occurs frequently after nasal surgery. N-methyl-D-aspartate (NMDA) receptor antagonists and analgesics, such as fentanyl, have been shown to prevent EA. Nefopam inhibits the NMDA receptor and shows a potent analge...

[Effect of dexmedetomidine on emergence agitation after general anesthesia in children undergoing odontotherapy in day-surgery operating room].

Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology
OBJECTIVE: To study the effectiveness of dexmedetomidine used for general anesthesia maintenance in children undergoing odontotherapy in day-surgery operating room in reducing the incidence of emergence agitation (EA).

Data-driven Machine Learning Models for Risk Stratification and Prediction of Emergence Delirium in Pediatric Patients Underwent Tonsillectomy/Adenotonsillectomy.

Annali italiani di chirurgia
AIM: In the pediatric surgical population, Emergence Delirium (ED) poses a significant challenge. This study aims to develop and validate machine learning (ML) models to identify key features associated with ED and predict its occurrence in children ...

Functional MRI-based machine learning strategy for prediction of postoperative delirium in cardiac surgery patients: A secondary analysis of a prospective observational study.

Journal of clinical anesthesia
STUDY OBJECTIVE: Delirium is a common complication after cardiac surgery and is associated with poor prognosis. An effective delirium prediction model could identify high-risk patients who might benefit from targeted prevention strategies. We introdu...

Comparison of machine learning and logistic regression models for predicting emergence delirium in elderly patients: A prospective study.

International journal of medical informatics
OBJECTIVE: To compare the performance of machine learning and logistic regression algorithms in predicting emergence delirium (ED) in elderly patients.