AIMC Topic: Monitoring, Intraoperative

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Machine learning for a combined electroencephalographic anesthesia index to detect awareness under anesthesia.

PloS one Aug 26, 2020
Spontaneous electroencephalogram (EEG) and auditory evoked potentials (AEP) have been suggested to monitor the level of consciousness during anesthesia. As both signals reflect different neuronal pathways, a combination of parameters from both signal...
Monitoring, Intraoperative Humans Support Vector Machine Neural Networks, Computer Monitoring, Physiologic Anesthesia, General Machine Learning Electroencephalography Algorithms Anesthetics, Intravenous Consciousness Evoked Potentials, Auditory Consciousness Monitors
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Artificial Intelligence in Echocardiography for Anesthesiologists.

Journal of cardiothoracic and vascular anesthesia Aug 24, 2020
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...
Artificial Intelligence Cardiovascular Diseases Echocardiography Monitoring, Intraoperative Anesthesiologists Humans
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Transthoracic echocardiography monitoring during ASD closure using an artificial hand system.

Cardiovascular ultrasound Jun 17, 2020
AIM: Continuous real-time echocardiographic monitoring is essential for guidance during ASD closure. However, transthoracic echocardiography (TTE) can only be implemented intermittently during fluoroscopy. We evaluate a novel approach to provide real...
Middle Aged Adolescent Child, Preschool Child Monitoring, Intraoperative Young Adult Adult Male Echocardiography Equipment Design Ultrasonography, Interventional Cardiac Catheterization Heart Septal Defects, Atrial Humans Artificial Intelligence Female
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Development of a prediction model for hypotension after induction of anesthesia using machine learning.

PloS one Apr 16, 2020
Arterial hypotension during the early phase of anesthesia can lead to adverse outcomes such as a prolonged postoperative stay or even death. Predicting hypotension during anesthesia induction is complicated by its diverse causes. We investigated the ...
Models, Cardiovascular Anesthetics Intubation, Intratracheal Middle Aged Risk Assessment Monitoring, Intraoperative ROC Curve Anesthesia, General Bayes Theorem Feasibility Studies Hypotension Cholecystectomy, Laparoscopic Arterial Pressure Female Aged Adult Humans Drug Delivery Systems Male Neural Networks, Computer Machine Learning Retrospective Studies Electronic Health Records
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A pilot trial of Convolution Neural Network for automatic retention-monitoring of capsule endoscopes in the stomach and duodenal bulb.

Scientific reports Mar 5, 2020
The retention of a capsule endoscope (CE) in the stomach and the duodenal bulb during the examination is a troublesome problem, which can make the medical staff spend several hours observing whether the CE enters the descending segment of the duodenu...
Humans Neural Networks, Computer Algorithms Retrospective Studies Female Image Processing, Computer-Assisted Duodenum Automation Capsule Endoscopy Stomach Capsule Endoscopes Foreign Bodies Sensitivity and Specificity Aged Male Aged, 80 and over Middle Aged Young Adult Adolescent Adult Monitoring, Intraoperative
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Near real-time intraoperative brain tumor diagnosis using stimulated Raman histology and deep neural networks.

Nature medicine Jan 6, 2020
Intraoperative diagnosis is essential for providing safe and effective care during cancer surgery. The existing workflow for intraoperative diagnosis based on hematoxylin and eosin staining of processed tissue is time, resource and labor intensive. M...
Neural Networks, Computer Algorithms Brain Neoplasms Deep Learning Computer Systems Humans Monitoring, Intraoperative Image Processing, Computer-Assisted Spectrum Analysis, Raman Probability Clinical Trials as Topic
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Representation learning in intraoperative vital signs for heart failure risk prediction.

BMC medical informatics and decision making Dec 9, 2019
BACKGROUND: The probability of heart failure during the perioperative period is 2% on average and it is as high as 17% when accompanied by cardiovascular diseases in China. It has been the most significant cause of postoperative death of patients. Ho...
Humans Neural Networks, Computer Machine Learning Sensitivity and Specificity Risk Assessment China Monitoring, Intraoperative Decision Trees Intraoperative Complications Area Under Curve Heart Failure Risk Vital Signs
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The use of a machine-learning algorithm that predicts hypotension during surgery in combination with personalized treatment guidance: study protocol for a randomized clinical trial.

Trials Oct 11, 2019
BACKGROUND: Intraoperative hypotension is associated with increased morbidity and mortality. Current treatment is mostly reactive. The Hypotension Prediction Index (HPI) algorithm is able to predict hypotension minutes before the blood pressure actua...
Surgical Procedures, Operative Arterial Pressure Intraoperative Period Randomized Controlled Trials as Topic Predictive Value of Tests Hypotension Netherlands Time Factors Machine Learning Monitoring, Intraoperative Humans Decision Support Techniques Blood Pressure Determination Prospective Studies Treatment Outcome Risk Factors Risk Assessment
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Machine learning for intraoperative prediction of viability in ischemic small intestine.

Physiological measurement Oct 24, 2018
OBJECTIVE: Evaluation of intestinal viability is essential in surgical decision-making in patients with acute intestinal ischemia. There has been no substantial change in the mortality rate (30%-93%) of patients with acute mesenteric ischemia (AMI) s...
Animals Ischemia Machine Learning Male Prognosis Monitoring, Intraoperative Jejunum Clinical Decision-Making Image Interpretation, Computer-Assisted Intestinal Diseases Female Electric Impedance Sus scrofa
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Identify and monitor clinical variation using machine intelligence: a pilot in colorectal surgery.

Journal of clinical monitoring and computing Sep 24, 2018
Standardized clinical pathways are useful tool to reduce variation in clinical management and may improve quality of care. However the evidence supporting a specific clinical pathway for a patient or patient population is often imperfect limiting ado...
Treatment Outcome Algorithms Humans Inflammatory Bowel Diseases Infusions, Intravenous Patient Compliance Reproducibility of Results Data Interpretation, Statistical Artificial Intelligence Patient Readmission Pilot Projects Signal Processing, Computer-Assisted Medical Informatics Machine Learning Monitoring, Intraoperative Colonic Neoplasms Colorectal Surgery Software Ketorolac
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