Artificial intelligence supported patient self-care in chronic heart failure: a paradigm shift from reactive to predictive, preventive and personalised care.
Matthew Barrett, Josiane Boyne, Julia Brandts, Hans-Peter Brunner-La Rocca, Lieven De Maesschalck, Kurt De Wit, Lana Dixon, Casper Eurlings, Donna Fitzsimons, Olga Golubnitschaja, Arjan Hageman, Frank Heemskerk, André Hintzen, Thomas M Helms, Loreena Hill, Thom Hoedemakers, Nikolaus Marx, Kenneth McDonald, Marc Mertens, Dirk Müller-Wieland Show all
EPMA Journal | Published : 2019
Heart failure (HF) is one of the most complex chronic disorders with high prevalence, mainly due to the ageing population and better treatment of underlying diseases. Prevalence will continue to rise and is estimated to reach 3% of the population in Western countries by 2025. It is the most important cause of hospitalisation in subjects aged 65 years or more, resulting in high costs and major social impact. The current "one-size-fits-all" approach in the treatment of HF does not result in best outcome for all patients. These facts are an imminent threat to good quality management of patients with HF. An unorthodox approach from a new vision on care is required. We propose a novel predictive,..View full abstract