AIMC Topic: Myocardial Infarction

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Real-time AI prediction for major adverse cardiac events in emergency department patients with chest pain.

Scandinavian journal of trauma, resuscitation and emergency medicine Sep 11, 2020
BACKGROUND: A big-data-driven and artificial intelligence (AI) with machine learning (ML) approach has never been integrated with the hospital information system (HIS) for predicting major adverse cardiac events (MACE) in patients with chest pain in ...
Young Adult Adult Sensitivity and Specificity Male Algorithms Humans Female Aged Artificial Intelligence Emergency Service, Hospital Myocardial Infarction Chest Pain Mortality Middle Aged Risk Assessment Models, Statistical Taiwan
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A Comparison of Three-Dimensional Speckle Tracking Echocardiography Parameters in Predicting Left Ventricular Remodeling.

Journal of healthcare engineering Jul 30, 2020
Three-dimensional speckle tracking echocardiography (3D STE) is an emerging noninvasive method for predicting left ventricular remodeling (LVR) after acute myocardial infarction (AMI). Previous studies analyzed the predictive value of 3D STE with tra...
Myocardial Infarction Sensitivity and Specificity Heart Ventricles Reproducibility of Results Area Under Curve Male Humans Ventricular Remodeling Echocardiography Coronary Angiography Machine Learning ROC Curve Risk Factors Ventricular Dysfunction, Left Middle Aged Percutaneous Coronary Intervention Aged Imaging, Three-Dimensional Female Models, Statistical Adult Predictive Value of Tests
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Prediction of 1-Year Mortality from Acute Myocardial Infarction Using Machine Learning.

The American journal of cardiology Jul 26, 2020
Risk stratification at hospital discharge could be instrumental in guiding postdischarge care. In this study, the risk models for 1-year mortality using machine learning (ML) were evaluated for guiding management of acute myocardial infarction (AMI) ...
Humans Machine Learning Algorithms Republic of Korea Time Factors ROC Curve Logistic Models Aged, 80 and over Predictive Value of Tests Male Registries Middle Aged Female Myocardial Infarction Risk Assessment Risk Factors Aged
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In-Hospital Prognostic Value of Electrocardiographic Parameters Other Than ST-Segment Changes in Acute Myocardial Infarction: Literature Review and Future Perspectives.

Heart, lung & circulation Jun 11, 2020
Electrocardiography (ECG) remains an irreplaceable tool in the management of the patients with myocardial infarction, with evaluation of the QRS and ST segment being the present major focus. Several ECG parameters have already been proposed to have p...
Inpatients Myocardial Infarction Prognosis Risk Factors Electrocardiography Humans Artificial Intelligence
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Myocardial infarction evaluation from stopping time decision toward interoperable algorithmic states in reinforcement learning.

BMC medical informatics and decision making Jun 1, 2020
BACKGROUND: The Elliot wave principle commonly characterizes the impulsive and corrective wave trends for both financial market trends and electrocardiograms. The impulsive wave trends of electrocardiograms can annotate several wave components of hea...
Humans Neural Networks, Computer Algorithms Electrocardiography Myocardial Infarction Heart Rate
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Application of a machine learning-driven, multibiomarker panel for prediction of incident cardiovascular events in patients with suspected myocardial infarction.

Biomarkers in medicine May 28, 2020
In patients with suspected myocardial infarction (MI), we sought to validate a machine learning-driven, multibiomarker panel for prediction of incident major adverse cardiovascular events (MACE). A previously described prognostic panel for MACE con...
Middle Aged Myocardial Infarction Aged Male Cardiovascular Diseases Humans Machine Learning Biomarkers Prognosis Female
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Performance of a convolutional neural network derived from an ECG database in recognizing myocardial infarction.

Scientific reports May 21, 2020
Artificial intelligence (AI) is developing rapidly in the medical technology field, particularly in image analysis. ECG-diagnosis is an image analysis in the sense that cardiologists assess the waveforms presented in a 2-dimensional image. We hypothe...
Artificial Intelligence Algorithms Databases, Factual Deep Learning Electrocardiography Myocardial Infarction Humans Neural Networks, Computer
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Integrating the STOP-BANG Score and Clinical Data to Predict Cardiovascular Events After Infarction: A Machine Learning Study.

Chest Apr 25, 2020
BACKGROUND: OSA conveys worse clinical outcomes in patients with coronary artery disease. The STOP-BANG score is a simple tool that evaluates the risk of OSA and can be added to the large number of clinical variables and scores that are obtained duri...
Risk Assessment Humans Aged Machine Learning Prospective Studies Male Myocardial Infarction Female Sleep Apnea, Obstructive Cardiovascular Diseases Middle Aged
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Development and application of artificial intelligence in cardiac imaging.

The British journal of radiology Feb 6, 2020
In this review, we describe the technical aspects of artificial intelligence (AI) in cardiac imaging, starting with radiomics, basic algorithms of deep learning and application tasks of algorithms, until recently the availability of the public databa...
Heart Ventricles Coronary Disease Vascular Calcification Computed Tomography Angiography Cardiomyopathies Coronary Stenosis Fractional Flow Reserve, Myocardial Magnetic Resonance Imaging Adipose Tissue Humans Heart Artificial Intelligence Myocardial Infarction Databases, Factual Algorithms Prognosis Deep Learning
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Are neural networks the ultimate risk prediction models in patients at high risk of acute myocardial infarction?

European journal of preventive cardiology Jan 28, 2020
Myocardial Infarction Humans Neural Networks, Computer Risk Assessment Predictive Value of Tests
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