BACKGROUND: Long-term opioid use has negative health care consequences. Patients who undergo surgery are at risk for prolonged opioid use after surgery (POUS). While risk factors have been previously identified, no methods currently exist to determin...
BACKGROUND: High-quality and high-utility feedback allows for the development of improvement plans for trainees. The current manual assessment of the quality of this feedback is time consuming and subjective. We propose the use of machine learning to...
BACKGROUND: Craniosynostosis is the premature fusion of ≥1 cranial sutures and often requires surgical intervention. Surgery may involve extensive osteotomies, which can lead to substantial blood loss. Currently, there are no consensus recommendation...
BACKGROUND: Induction of anesthesia is a phase characterized by rapid changes in both drug concentration and drug effect. Conventional mammillary compartmental models are limited in their ability to accurately describe the early drug distribution kin...
BACKGROUND: Cardiovascular waveforms contain information for clinical diagnosis. By learning and organizing the subtle change of waveform morphology from large amounts of raw waveform data, unsupervised manifold learning helps delineate a high-dimens...
Artificial intelligence-driven anesthesiology and perioperative care may just be around the corner. However, its promises of improved safety and patient outcomes can only become a reality if we take the time to examine its technical, ethical, and mor...
BACKGROUND: Brain monitors tracking quantitative brain activities from electroencephalogram (EEG) to predict hypnotic levels have been proposed as a labor-saving alternative to behavioral assessments. Expensive clinical trials are required to validat...
BACKGROUND: Predictive analytics systems may improve perioperative care by enhancing preparation for, recognition of, and response to high-risk clinical events. Bradycardia is a fairly common and unpredictable clinical event with many causes; it may ...