Machine learning versus conventional clinical methods in guiding management of heart failure patients-a systematic review.

"Conflict of interest The authors declare that they have no conflicts of interest."

"Funding information The work was supported by a Grand-in-Aid (#15GRNT23070001) from the American Heart Association (AHA), the Institute of Precision Medicine (17UNPG33840017) from the AHA, the RICBAC Foundation, NIH grant 1 R01 HL135335-01, 1 R21 HL137870-01, and 1 R21EB026164-01. This work was conducted with support from Harvard Catalyst, The Harvard Clinical and Translational Science Center (National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health Award 8UL1TR000170-05 and financial contributions from Harvard University and its affiliated academic health care centers). The content is solely the responsibility of the authors and does not necessarily represent the official views of Harvard Catalyst, Harvard University and its affiliated academic health care centers or the National Institutes of Health."