tycheheart is a data-centric approach to individualized patient management regarding mortality, re-hospitalisations and quality of life (QoL) in outpatients with CHF.


• By using of non-invasive monitoring and a continuous risk assessement with traditional and ancillary clinical data sources, we re-invent CHF management.
• Definition of the point of autonomous adaptation long before symptoms occur.
• Integration of data based decision making into the clinical outpatient workflow and the use of advanced machine learning.
• Collection of better and more complex real life data by continuous, non-invasive monitoring of the disease and creating a personalised tech-platform.
• Mapping the digital phenotype, analysing the genetical sequence of CHF and detecting digital biomarkers for the development of a patient-centralised and tailored medicine.


Heart failure management through continuous, non-invasive monitoring and stratification of risks using traditional prameters plus 24/7-recording, -collecting and -analysing data from wearables by a self-learning algorhythm and database (A.I.).
• Portable and affordable external sensors, connected to smart devices, have increased the possibilities for 24/7 monitoring.
• This procedure and the use of a risk score, built with clinical and non-clinical data and a self-learning algorithm, helps to detect early signs of cardiac de-compensation and allows the optimisation of and adherence to treatments in CHF.
• Blood samples will be taken to gather information about biomarkers, anti-heart-antibodies and a sequential analysis of the genome.


• It is expected that re-hospitalisation rates will be reduced and that prognosis, quality of life, medical compliance and the knowledge about the disease will be improved.
• Furthermore, the pheno-type and the geno-type of CHF-syndrome will be described percisely.
• By overlaying both, a tailored and individualized treatment can be developed in the future.