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

BackgroundArtificial 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.MethodsThe study approved by the institutional review board, aimed at the RTs working in the Kingdom of Saudi Arabia. The validated questionnaire collected reflective insights from 448 RTs in Saudi Arabia. Descriptive statistics, thematic analysis, Fisher’s exact test, and chi-square test were used to evaluate the significance of the data.ResultsThe survey revealed a nearly equal distribution of genders (51% female, 49% male). Most respondents were in the 20–25 age group (54%), held bachelor’s degrees (69%), and had 0–5 years of experience (73%). While 28% had some knowledge of AI, only 8.5% had practical experience. Significant gender disparities in AI knowledge were noted (p