Heart Failure Data

A dataset containing the ages and other attributes of almost 300 cases.

data(heartfailure)

Format

A data frame with 299 rows and 13 variables. The variables are as follows:

age

patient's age.

anaemia

decrease of red blood cells or hemoglobin (boolean), Yes, No.

cpk_enzyme

level of the CPK(creatinine phosphokinase) enzyme in the blood (mcg/L).

diabetes

if the patient has diabetes (boolean), Yes, No.

ejection_fraction

percentage of blood leaving the heart at each contraction (percentage).

hblood_pressure

high_blood_pressure. if the patient has hypertension (boolean), Yes, No.

platelets

platelets in the blood (kiloplatelets/mL).

creatinine

level of serum creatinine in the blood (mg/dL).

sodium

level of serum sodium in the blood (mEq/L).

sex

patient's sex (binary), Male, Female.

smoking

if the patient smokes or not (boolean), Yes, No.

time

follow-up period (days).

death_event

if the patient deceased during the follow-up period (boolean), Yes, No.

Source

"Heart Failure Prediction" in Kaggle <https://www.kaggle.com/andrewmvd/heart-failure-clinical-data>, License : CC BY 4.0

Details

Heart failure is a common event caused by Cardiovascular diseasess and this dataset contains 12 features that can be used to predict mortality by heart failure.

References

Davide Chicco, Giuseppe Jurman: Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone. BMC Medical Informatics and Decision Making 20, 16 (2020). <https://doi.org/10.1186/s12911-020-1023-5>