Applications of artificial intelligence in emergency and critical care diagnostics: a systematic review and meta-analysis.

Introduction: Artificial intelligence has come to be the highlight in almost all fields of science. It uses various models and algorithms to detect patterns and specific findings to diagnose a disease with utmost accuracy. With the increasing need for accurate and precise diagnosis of disease, employing artificial intelligence models and concepts in healthcare setup can be beneficial.

Artificial intelligence in respiratory care: knowledge, perceptions, and practices-a cross-sectional study.

Background: Artificial intelligence (AI) is reforming healthcare, particularly in respiratory medicine and critical care, by utilizing big and synthetic data to improve diagnostic accuracy and therapeutic benefits. This survey aimed to evaluate the knowledge, perceptions, and practices of respiratory therapists (RTs) regarding AI to effectively incorporate these technologies into the clinical practice.

Methods: The study approved by the institutional review board, aimed at the RTs working in the Kingdom of Saudi Arabia.

Simulation-Based Teaching and Learning in Respiratory Care Education: A Narrative Review.

Simulation-based pedagogy has become an essential aspect of healthcare education. However, there is a significant gap in the literature regarding the application of simulation-based modalities in respiratory care education. This review aims to address this gap by providing insight into the theory and current uses of simulation, its effectiveness in respiratory care education, and strategies to enhance faculty development.