Fig. 2: Unsupervised ML and Mitral valve regurgitation. | npj Cardiovascular Health

Fig. 2: Unsupervised ML and Mitral valve regurgitation.

From: Phenotyping valvular heart diseases using the lens of unsupervised machine learning: a scoping review

Fig. 2

Multi-component unsupervised machine algorithms are utilized in patients with primary and secondary mitral valve regurgitation (MR). In primary MR along with severity of regurgitation, left atrial size and strain as well as presence of LV diastolic dysfunction identified patients progressing to myocardial fibrosis and LV systolic dysfunction and predicted worse outcomes. In patients with secondary MR, ML algorithms have identified patients who would benefit from trans-catheter treatment.

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