Machine learning (ML) is revolutionizing anesthesiology research. Unlike classical research methods that are largely inference-based, ML is geared more towards making accurate predictions. ML is a field of artificial intelligence concerned with devel...
Perioperative morbidity is a public health priority, and surgical volume is increasing rapidly. With advances in technology, there is an opportunity to research the utility of a telemedicine-based control center for anesthesia clinicians that assess...
The widely used American Society of Anesthesiologists Physical Status (ASA PS) classification is subjective, requires manual clinician review to score, and has limited granularity. Our objective was to develop a system that automatically generates an...
OBJECTIVE: The angle of the C-MAC D-Blade videolaryngoscope, which is used for difficult airway interventions, is not compatible with routinely used endotracheal tubes.
BACKGROUND: A new anesthesia system, the E-CAIOVX (GE Healthcare) enables the continuous monitoring of oxygen consumption (VO2) and carbon dioxide elimination (VCO2) during the surgical operation. The aim of this study was to evaluate the prognostic ...
Anesthesiology has a longstanding commitment to patient safety, characterized by innovative research, quality improvement, multidisciplinary collaboration, and engineering-based approaches to care systems. The field has been instrumental in advancing...
The emergence of artificial intelligence (AI)-based linguistic models has revolutionized academic writing, prompting concerns about integrity. In response, AI-powered text authenticity detectors have been developed. This study examines AI tool usage ...
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