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Company
About Us
Careers
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Publications
News
Podcasts
Company
About Us
Careers
Resources
Publications
News
Podcasts
Publications
Heart Failure
1.
Multicenter validation of a machine learning phase space electro-mechanical pulse wave analysis to predict elevated left ventricular end diastolic pressure at the point-of-care
2.
Identifying Novel Phenotypes of Elevated Left Ventricular End Diastolic Pressure Using Hierarchical Clustering of Features Derived From Electromechanical Waveform Data
3.
Machine learning: at the heart of failure diagnosis
4.
Predicting cardiac disease from interactions of simultaneously-acquired hemodynamic and cardiac signals
5.
First-In-Man Development of a Machine Learning Analytics Approach to Predict Elevated Left Ventricular Pressures
6.
Coronary Artery Disease Learning and Algorithm Development Study: Early Analysis of Ejection Fraction Evaluation
Coronary Artery Disease
1.
Development and validation of a machine learned algorithm to IDENTIFY functionally significant coronary artery disease
2.
Cardiac Phase Space Analysis: Assessing Coronary Artery Disease Utilizing Artificial Intelligence
3.
Predicting cardiac disease from interactions of simultaneously-acquired hemodynamic and cardiac signals
4.
Cardiac Phase Space Tomography: A novel method of assessing coronary artery disease utilizing machine learning
5.
TCT-232 Diagnostic Accuracy of Machine Learned Algorithms Utilizing a Novel Form of Cardiac Phase Tomography (cPST) versus Single Photon Emission Tomography (SPECT) in the Assessment of CAD
6.
TCT-233 Machine-Learned Algorithms Utilizing Novel Tomography for Evaluating Coronary Artery Disease
7.
Noninvasive Detection of Coronary Artery Disease Using Resting Phase Signals and Advanced Machine Learning
8.
TCT-154 Gender based Assessment of Coronary Artery Disease by Cardiac Phase Tomography Using Machine-Learned Algorithms
9.
TCT-177 Assessing Coronary Artery Disease by Cardiac Phase Tomography Using Machine-Learned Algorithms in Obese and Elderly Subjects
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