AI Medical Compendium Topic

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Monitoring, Intraoperative

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Tailored Intraoperative MRI Strategies in High-Grade Glioma Surgery: A Machine Learning-Based Radiomics Model Highlights Selective Benefits.

Operative neurosurgery (Hagerstown, Md.)
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 in Echocardiography for Anesthesiologists.

Journal of cardiothoracic and vascular anesthesia
Echocardiography is a unique diagnostic tool for intraoperative monitoring and assessment of patients with cardiovascular diseases. However, there are high levels of interoperator variations in echocardiography interpretations that could lead to inac...

Recurrent laryngeal nerve monitoring during totally robot-assisted Ivor Lewis esophagectomy.

Langenbeck's archives of surgery
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...

Deep learning models for the prediction of intraoperative hypotension.

British journal of anaesthesia
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.

Tool-tissue force segmentation and pattern recognition for evaluating neurosurgical performance.

Scientific reports
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...

Continuous Blood Pressure Monitoring in Patients Having Surgery: A Narrative Review.

Medicina (Kaunas, Lithuania)
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...

Artificial intelligence and its clinical application in Anesthesiology: a systematic review.

Journal of clinical monitoring and computing
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...

Utilising intraoperative respiratory dynamic features for developing and validating an explainable machine learning model for postoperative pulmonary complications.

British journal of anaesthesia
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
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...