Maskininlärning för prediktion av dödlighet och hospitalisering hos hjärtsviktspatienter
Heart failure is one of the most common causes of hospitalization in Sweden, and 30\% of all heart failure patients need unplanned readmissions within three months, creating a burden on the healthcare system. This project was conducted within the healthcare model "Hospital at Home", where there is currently no systematic follow-up method of heart failure patients. By monitoring those wit
