artificial intelligence for your health

heart failure explorer

HeartFailure Explorer is an Artificial Intelligence model based test which supports individual therapy of heart failure.

The test provides a risk prediction and therapy proposal which optimizes treatment effect and considers co-morbidities and adverse effects on an individual patient level.

Our beta version of HeartFailure Explorer has been developed together with Prof. Hans-Peter Brunner at the cardiology department, Maastricht University.

 





ROC Curves for models with endpoints death (Death) and hospitalization due to heart failure (EP_hosp_HF) and the combined model.






Previous therapies

At the present time medical guidelines recommend the following heart failure therapy: ACE inhibitor, b-blocker, eperelone, loop diuretic. If patients do not satisfyingly respond to the therapy, the cardiologist has to alter the dosage of medication in trial and error mode, navigating through a difficult field of different other impacts like adverse effects trough the increased dosage of certain drugs, or conspicuous conflicts with other medication. For those patients residence costs can dramatically increase due to a not appropriate therapy.

We applied the HeartFailure models also to data of the PROTECT study of the Heart Center, Massachusetts General Hospital Boston. First tests have confirmed the former results.