2. Predicting cardiac disease from interactions of simultaneously-acquired hemodynamic and cardiac signals
3. First-In-Man Development of a Machine Learning Analytics Approach to Predict Elevated Left Ventricular Pressures
4. Coronary Artery Disease Learning and Algorithm Development Study: Early Analysis of Ejection Fraction Evaluation
1. Predicting cardiac disease from interactions of simultaneously-acquired hemodynamic and cardiac signals
2. Cardiac Phase Space Tomography: A novel method of assessing coronary artery disease utilizing machine learning
3. 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
4. TCT-233 Machine-Learned Algorithms Utilizing Novel Tomography for Evaluating Coronary Artery Disease
5. Noninvasive Detection of Coronary Artery Disease Using Resting Phase Signals and Advanced Machine Learning
6. TCT-154 Gender based Assessment of Coronary Artery Disease by Cardiac Phase Tomography Using Machine-Learned Algorithms
7. TCT-177 Assessing Coronary Artery Disease by Cardiac Phase Tomography Using Machine-Learned Algorithms in Obese and Elderly Subjects