AIMC Topic: Cardiomyopathies

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Can Generative AI Learn Physiological Waveform Morphologies? A Study on Denoising Intracardiac Signals in Ischemic Cardiomyopathy.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Reducing electrophysiological (EP) signal noise is essential for diagnosis, mapping, and ablation, yet traditional approaches are suboptimal. This study tests the hypothesis that generative artificial intelligence (AI), specifically Variational Autoe...

Machine learning and network medicine: a novel approach for precision medicine and personalized therapy in cardiomyopathies.

Journal of cardiovascular medicine (Hagerstown, Md.)
The early identification of pathogenic mechanisms is essential to predict the incidence and progression of cardiomyopathies and to plan appropriate preventive interventions. Noninvasive cardiac imaging such as cardiac computed tomography, cardiac mag...

[Automated Classification of Calcification and Stent on Computed Tomography Coronary Angiography Using Deep Learning].

Nihon Hoshasen Gijutsu Gakkai zasshi
In computed tomography coronary angiography (CTCA), calcification and stent make it difficult to evaluate intravascular lumen. This is a cause of low positive-predictive value of coronary stenosis. Therefore, it is expected to develop a computer-aide...

[Perfusion-Metabolic Myocardial Scintigraphy in Prognosis of Left Ventricular Remodeling After Complex Surgical Treatment of Ischemic Cardiomyopathy].

Kardiologiia
PURPOSE: To study capabilities of perfusion-metabolic myocardial scintigraphy for prediction of the left ventricular (LV) reverse remodeling after comprehensive surgical treatment of ischemic cardiomyopathy (ICMP).