AIMC Topic: Cardiac Surgical Procedures

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Ensemble machine learning prediction and variable importance analysis of 5-year mortality after cardiac valve and CABG operations.

Scientific reports
Despite having a similar post-operative complication profile, cardiac valve operations are associated with a higher mortality rate compared to coronary artery bypass grafting (CABG) operations. For long-term mortality, few predictors are known. In th...

Machine learning prediction models for prognosis of critically ill patients after open-heart surgery.

Scientific reports
We aimed to build up multiple machine learning models to predict 30-days mortality, and 3 complications including septic shock, thrombocytopenia, and liver dysfunction after open-heart surgery. Patients who underwent coronary artery bypass surgery, a...

Detecting neurodevelopmental trajectories in congenital heart diseases with a machine-learning approach.

Scientific reports
We aimed to delineate the neuropsychological and psychopathological profiles of children with congenital heart disease (CHD) and look for associations with clinical parameters. We conducted a prospective observational study in children with CHD who u...

Predicting the Development of Surgery-Related Pressure Injury Using a Machine Learning Algorithm Model.

The journal of nursing research : JNR
BACKGROUND: Surgery-related pressure injury (SRPI) is a serious problem in patients who undergo cardiovascular surgery. Identifying patients at a high risk of SRPI is important for clinicians to recognize and prevent it expeditiously. Machine learnin...

A conservative screening algorithm to determine candidacy for robotic mitral valve surgery.

The Journal of thoracic and cardiovascular surgery
OBJECTIVE: Patient selection for robotically assisted mitral valve repair remains controversial. We assessed outcomes of a conservative screening algorithm developed to select patients with degenerative mitral valve disease for robotic surgery.

Artificial intelligence in cardiothoracic surgery.

Minerva cardioangiologica
The tremendous and rapid technological advances that humans have achieved in the last decade have definitely impacted how surgical tasks are performed in the operating room (OR). As a high-tech work environment, the contemporary OR has incorporated n...

Machine learning improves mortality risk prediction after cardiac surgery: Systematic review and meta-analysis.

The Journal of thoracic and cardiovascular surgery
BACKGROUND: Interest in the usefulness of machine learning (ML) methods for outcomes prediction has continued to increase in recent years. However, the advantage of advanced ML model over traditional logistic regression (LR) remains controversial. We...

Prediction of the development of acute kidney injury following cardiac surgery by machine learning.

Critical care (London, England)
BACKGROUND: Cardiac surgery-associated acute kidney injury (CSA-AKI) is a major complication that results in increased morbidity and mortality after cardiac surgery. Most established prediction models are limited to the analysis of nonlinear relation...