scholarly journals TCT-231 An artificial intelligence based solution for fully automated cardiac phase and end-diastolic frame detection on coronary angiographies

2018 ◽  
Vol 72 (13) ◽  
pp. B96-B97
Author(s):  
Costin Ciusdel ◽  
Alexandru Turcea ◽  
Andrei Puiu ◽  
Lucian Itu ◽  
Lucian Calmac ◽  
...  
2021 ◽  
Vol 2021 ◽  
pp. 1-5
Author(s):  
Mark G. Rabbat ◽  
Shyam Ramchandani ◽  
William E. Sanders

The bridge of artificial intelligence to cardiovascular medicine has opened up new avenues for novel diagnostics that may significantly enhance the cardiology care pathway. Cardiac phase space analysis is a noninvasive diagnostic platform that combines advanced disciplines of mathematics and physics with machine learning. Thoracic orthogonal voltage gradient (OVG) signals from an individual are evaluated by cardiac phase space analysis to quantify physiological and mathematical features associated with coronary stenosis. The analysis is performed at the point of care without the need for a change in physiologic status or radiation. This review will highlight some of the scientific principles behind the technology, provide a description of the system and device, and discuss the study procedure, clinical data, and potential future applications.


Author(s):  
David L. Poole ◽  
Alan K. Mackworth

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