AIMC Topic: Monitoring, Intraoperative
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Predicting vital sign deviations during surgery from patient monitoring data: developing and validating single-stream deep learning models.
British journal of anaesthesia
Aug 1, 2024
Utilising intraoperative respiratory dynamic features for developing and validating an explainable machine learning model for postoperative pulmonary complications. Comment on Br J Anaesth 2024; 132: 1315-26.
British journal of anaesthesia
Jul 15, 2024
Utilising intraoperative respiratory dynamic features for developing and validating an explainable machine learning model for postoperative pulmonary complications.
British journal of anaesthesia
Apr 18, 2024
BACKGROUND: Timely detection of modifiable risk factors for postoperative pulmonary complications (PPCs) could inform ventilation strategies that attenuate lung injury. We sought to develop, validate, and internally test machine learning models that ...
Machine learning based analysis and detection of trend outliers for electromyographic neuromuscular monitoring.
Journal of clinical monitoring and computing
Apr 4, 2024
PURPOSE: Neuromuscular monitoring is frequently plagued by artefacts, which along with the frequent unawareness of the principles of this subtype of monitoring by many clinicians, tends to lead to a cynical attitute by clinicians towards these monito...
Tailored Intraoperative MRI Strategies in High-Grade Glioma Surgery: A Machine Learning-Based Radiomics Model Highlights Selective Benefits.
Operative neurosurgery (Hagerstown, Md.)
Dec 22, 2023
BACKGROUND AND OBJECTIVES: In high-grade glioma (HGG) surgery, intraoperative MRI (iMRI) has traditionally been the gold standard for maximizing tumor resection and improving patient outcomes. However, recent Level 1 evidence juxtaposes the efficacy ...
Artificial intelligence and its clinical application in Anesthesiology: a systematic review.
Journal of clinical monitoring and computing
Oct 21, 2023
PURPOSE: Application of artificial intelligence (AI) in medicine is quickly expanding. Despite the amount of evidence and promising results, a thorough overview of the current state of AI in clinical practice of anesthesiology is needed. Therefore, o...
Continuous Blood Pressure Monitoring in Patients Having Surgery: A Narrative Review.
Medicina (Kaunas, Lithuania)
Jul 14, 2023
Hypotension can occur before, during, and after surgery and is associated with postoperative complications. Anesthesiologists should thus avoid profound and prolonged hypotension. A crucial part of avoiding hypotension is accurate and tight blood pre...
Tool-tissue force segmentation and pattern recognition for evaluating neurosurgical performance.
Scientific reports
Jun 13, 2023
Surgical data quantification and comprehension expose subtle patterns in tasks and performance. Enabling surgical devices with artificial intelligence provides surgeons with personalized and objective performance evaluation: a virtual surgical assist...
Deep learning models for the prediction of intraoperative hypotension.
British journal of anaesthesia
Feb 6, 2021
BACKGROUND: Intraoperative hypotension is associated with a risk of postoperative organ dysfunction. In this study, we aimed to present deep learning algorithms for real-time predictions 5, 10, and 15 min before a hypotensive event.
Recurrent laryngeal nerve monitoring during totally robot-assisted Ivor Lewis esophagectomy.
Langenbeck's archives of surgery
Sep 24, 2020
PURPOSE: The robot-assisted approach for Ivor Lewis esophagectomy offers an enlarged, three-dimensional overview of the intraoperative situs. The vagal nerve (VN) can easily be detected, preserved, and intentionally resected below the separation poin...
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