A data frame with 299 observations on the following 13 variables.
age
a numeric vector
anaemia
a numeric vector
creatinine_phosphokinase
a numeric vector
diabetes
a numeric vector
ejection_fraction
a numeric vector
high_blood_pressure
a numeric vector
platelets
a numeric vector
serum_creatinine
a numeric vector
serum_sodium
a numeric vector
sex
a numeric vector
smoking
a numeric vector
time
a numeric vector
DEATH_EVENT
a numeric vector
Details
This dataset contains the medical records of 299 patients who had heart failure, collected during their follow-up period, where each patient profile has 13 clinical features.
References
Davide Chicco, Giuseppe Jurman. (2020). Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone. BMC Medical Informatics and Decision Making.