AIMC Topic: Myocardial Infarction

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Artificial Intelligence Uncovered Clinical Factors for Cardiovascular Events in Myocardial Infarction Patients with Glucose Intolerance.

Cardiovascular drugs and therapy Aug 1, 2020
PURPOSE: Glucose intolerance (GI), defined as either prediabetes or diabetes, promotes cardiovascular events in patients with myocardial infarction (MI). Using the pooled clinical data from patients with MI and GI in the completed ABC and PPAR trials...
Randomized Controlled Trials as Topic Percutaneous Coronary Intervention Coronary Artery Disease Proton Pump Inhibitors Recurrence Myocardial Infarction Heart Failure Angina, Stable Data Mining Male Glucose Intolerance Humans Middle Aged Natriuretic Peptide, Brain Biomarkers Artificial Intelligence Blood Glucose Prognosis Databases, Factual Female Retrospective Studies Hospitalization Risk Factors Aged
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A Composite Material Based Neural Network for Tissue Mechanical Properties Estimation Toward Stage Assessment of Infarction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Cardiac biomechanical modelling is a promising new tool to be used in prognostic medicine and therapy planning for patients suffering from a variety of cardiovascular diseases and injuries. In order to have an accurate biomechanical model, personaliz...
Humans Neural Networks, Computer Wound Healing Cicatrix Myocardial Infarction Collagen
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Human endurance and AI: Audentes Fortna Iuvat - fortune favours the bold.

Perfusion Nov 1, 2019
Extracorporeal Membrane Oxygenation Myocardial Infarction Cardiopulmonary Bypass Running Artificial Intelligence Interleukins Postoperative Hemorrhage Achievement Fibrinogen Physical Endurance Lactic Acid Humans
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Myocardial Infarction Detection Based on Multi-lead Ensemble Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Automatic myocardial infarction (MI) detection using an electrocardiogram (ECG) is of great significance for improving the survival rate of patients. In this study, we propose a multi-lead ensemble neural network (MENN) to distinguish anterior myocar...
Neural Networks, Computer Algorithms Sensitivity and Specificity Myocardial Infarction Diagnosis, Computer-Assisted Electrocardiography Humans
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MIRKB: a myocardial infarction risk knowledge base.

Database : the journal of biological databases and curation Jan 1, 2019
Myocardial infarction (MI) is a common cardiovascular disease and a leading cause of death worldwide. The etiology of MI is complicated and not completely understood. Many risk factors are reported important for the development of MI, including lifes...
Myocardial Infarction Knowledge Bases Humans Databases, Factual
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Serum Aldosterone as Predictor of Progression of Coronary Heart Disease in Patients Without Signs of Heart Failure After Acute Myocardial Infarction.

Medical archives (Sarajevo, Bosnia and Herzegovina) Dec 1, 2018
INTRODUCTION: In patients with acute myocardial infarction (AMI) early risk assessment of development of complications is of great importance. It is proven that aldosterone level has a major role in progression of cardiovascular pathology.
Middle Aged Coronary Disease Risk Assessment Female Myocardial Infarction Disease Progression Follow-Up Studies Aged Aldosterone Humans Predictive Value of Tests Male Biomarkers Prognosis
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Letter to the Editor concerning the article "Machine learning for prediction of 30-day mortality after ST elevation myocardial infarction".

International journal of cardiology Sep 1, 2018
Myocardial Infarction Electrocardiography ST Elevation Myocardial Infarction Humans Machine Learning
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Texture Analysis and Machine Learning for Detecting Myocardial Infarction in Noncontrast Low-Dose Computed Tomography: Unveiling the Invisible.

Investigative radiology Jun 1, 2018
OBJECTIVES: The aim of this study was to test whether texture analysis and machine learning enable the detection of myocardial infarction (MI) on non-contrast-enhanced low radiation dose cardiac computed tomography (CCT) images.
Humans Machine Learning Retrospective Studies Heart Reproducibility of Results Myocardial Infarction Aged Male Tomography, X-Ray Computed Radiation Dosage Aged, 80 and over Female Middle Aged Cluster Analysis Adult Diagnosis, Differential Sensitivity and Specificity
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Deep learning sharpens views of cells and genes.

Nature Jan 4, 2018
Image Processing, Computer-Assisted Myocardial Infarction Retina Machine Learning Neoplasms Gene Expression Profiling Humans Neural Networks, Computer
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Machine Learning in Health Care.

National Bureau of Economic Research bulletin on aging and health Jan 1, 2018
Algorithms Decision Support Techniques Delivery of Health Care Humans Machine Learning Unnecessary Procedures Decision Making, Computer-Assisted Risk Factors Myocardial Infarction Cost-Benefit Analysis
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