Cardiovascular

Myocardial Infarction

Latest AI and machine learning research in myocardial infarction for healthcare professionals.

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Showing 1219-1239 of 7,963 articles
Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network.

Computerized electrocardiogram (ECG) interpretation plays a critical role in the clinical ECG workfl...

Jan 2019 30617320
AF detection from ECG recordings using feature selection, sparse coding, and ensemble learning.

OBJECTIVE: The objective of this paper is to provide an algorithm for accurate, automated detection ...

Dec 2018 30524091
Automated beat-wise arrhythmia diagnosis using modified U-net on extended electrocardiographic recordings with heterogeneous arrhythmia types.

Abnormality of the cardiac conduction system can induce arrhythmia - abnormal heart rhythm - that ca...

Dec 2018 30599317
Cardiac Troponin I: Ultrasensitive Detection Using Faradaic Electrochemical Impedance.

An electrochemical biosensor for the detection of cardiac troponin I, cTnI, an important cardiac bio...

Dec 2018 31458332
A Unique Case of Severe Anemia Secondary to Copper Deficiency in an Adult Patient.

Anemia is a frequently encountered problem in the healthcare system. Common causes of anemia include...

Nov 2018 30723637
Localization of Ventricular Activation Origin from the 12-Lead ECG: A Comparison of Linear Regression with Non-Linear Methods of Machine Learning.

We have previously developed an automated localization method based on multiple linear regression (M...

Nov 2018 30465152
A deep neural network learning algorithm outperforms a conventional algorithm for emergency department electrocardiogram interpretation.

BACKGROUND: Cardiologs® has developed the first electrocardiogram (ECG) algorithm that uses a deep n...

Nov 2018 30476648
Motion artifact recognition and quantification in coronary CT angiography using convolutional neural networks.

Excellent image quality is a primary prerequisite for diagnostic non-invasive coronary CT angiograph...

Nov 2018 30471464
Deep Deterministic Learning for Pattern Recognition of Different Cardiac Diseases through the Internet of Medical Things.

Electrocardiography (ECG) sensors play a vital role in the Internet of Medical Things, and these sen...

Nov 2018 30397730
Ensembling convolutional and long short-term memory networks for electrocardiogram arrhythmia detection.

OBJECTIVE: Atrial fibrillation is a common type of heart rhythm abnormality caused by a problem with...

Oct 2018 30010088
A Machine-Learning Approach for Detection and Quantification of QRS Fragmentation.

OBJECTIVE: Fragmented QRS (fQRS) is an accessible biomarker and indication of myocardial scarring th...

Oct 2018 30371397
A convolutional neural network for ECG annotation as the basis for classification of cardiac rhythms.

OBJECTIVE: Electrocardiography is the most common tool to diagnose cardiovascular diseases. Annotati...

Oct 2018 30235165
ECG Signal Classification Using Various Machine Learning Techniques.

Electrocardiogram (ECG) signal is a process that records the heart rate by using electrodes and dete...

Oct 2018 30334106
ECG authentication system design incorporating a convolutional neural network and generalized S-Transformation.

Electrocardiogram (ECG) is gaining increased attention as a biometric method in a wide range of appl...

Sep 2018 30290297
ECG signal classification for the detection of cardiac arrhythmias using a convolutional recurrent neural network.

OBJECTIVE: The electrocardiogram (ECG) provides an effective, non-invasive approach for clinical dia...

Sep 2018 30102248
Towards End-to-End ECG Classification With Raw Signal Extraction and Deep Neural Networks.

This paper proposes deep learning methods with signal alignment that facilitate the end-to-end class...

Sep 2018 30235153
Analytical Concordance of Diverse Point-of-Care and Central Laboratory Troponin I Assays.

BACKGROUND: Cardiac troponin I (cTnI) 99th percentile cutoffs, used in the diagnosis of acute myocar...

Sep 2018 31639752
Multi-stage SVM approach for cardiac arrhythmias detection in short single-lead ECG recorded by a wearable device.

OBJECTIVE: Use of wearable ECG devices for arrhythmia screening is limited due to poor signal qualit...

Sep 2018 30102239
Parallel use of a convolutional neural network and bagged tree ensemble for the classification of Holter ECG.

UNLABELLED: The automated detection of arrhythmia in a Holter ECG signal is a challenging task due t...

Sep 2018 30102251
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