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Cardiac Surgical Procedures

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Stress Echocardiographic Evaluation for D-Transposition of the Great Arteries after Atrial Redirection: Unmasking Early Signs of Myocardial Dysfunction and Baffle Stenosis.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
BACKGROUND: The authors used semisupine cycle ergometry stress echocardiography to assess cardiac function and unmask baffle stenosis in patients with d-transposition of the great arteries after atrial redirection surgery.

Neural Network Prediction of ICU Length of Stay Following Cardiac Surgery Based on Pre-Incision Variables.

PloS one
BACKGROUND: Advanced predictive analytical techniques are being increasingly applied to clinical risk assessment. This study compared a neural network model to several other models in predicting the length of stay (LOS) in the cardiac surgical intens...

Totally robotic repair of atrioventricular septal defect in the adult.

Journal of cardiothoracic surgery
BACKGROUND: Atrioventricular septal defect (AVSD) accounts for up to 3 % of congenital cardiac defects, which is routinely repaired via median sternotomy. Minimally invasive approach such as endoscopic or robotic assisted repair for AVSD has not been...

Robot-Assisted Training Early After Cardiac Surgery.

Journal of cardiac surgery
BACKGROUND: To assess feasibility and safety of a robot-assisted gait therapy with the LokomatĀ® system in patients early after open heart surgery.

Clinical time series prediction: Toward a hierarchical dynamical system framework.

Artificial intelligence in medicine
OBJECTIVE: Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventi...

A novel generative multi-task representation learning approach for predicting postoperative complications in cardiac surgery patients.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Early detection of surgical complications allows for timely therapy and proactive risk mitigation. Machine learning (ML) can be leveraged to identify and predict patient risks for postoperative complications. We developed and validated the...

Machine Learning with Clinical and Intraoperative Biosignal Data for Predicting Cardiac Surgery-Associated Acute Kidney Injury.

Studies in health technology and informatics
Early identification of patients at high risk of cardiac surgery-associated acute kidney injury (CSA-AKI) is crucial for its prevention. We aimed to leverage perioperative clinical and intraoperative biosignal data to develop machine learning models ...

Using machine learning to predict bleeding after cardiac surgery.

European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery
OBJECTIVES: The primary objective was to predict bleeding after cardiac surgery with machine learning using the data from the Australia New Zealand Society of Cardiac and Thoracic Surgeons Cardiac Surgery Database, cardiopulmonary bypass perfusion da...