Machine learning to support decision-making for cardiac surgery during the acute phase of infective endocarditis
Rapid identification of patients at high risk of death may trigger additional therapeutic interventions, which in turn may change the course of the disease and improve prognosis. For infective endocarditis (IE), inhospital mortality rate remains high—from 15% to 30%—despite major achievements over the last 20 years in diagnostic tools (imaging, microbiology) and cardiac surgery.
The endocarditis team is a great innovation strongly supported by recent guidelines from America and Europe: The American 2015 guidelines
Publisher URL: http://heart.bmj.com/cgi/content/short/103/18/1396
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