A dataset containing the ages and other attributes of almost 300 cases.
A data frame with 299 rows and 13 variables. The variables are as follows:
decrease of red blood cells or hemoglobin (boolean), Yes, No.
level of the CPK(creatinine phosphokinase) enzyme in the blood (mcg/L).
if the patient has diabetes (boolean), Yes, No.
percentage of blood leaving the heart at each contraction (percentage).
high_blood_pressure. if the patient has hypertension (boolean), Yes, No.
platelets in the blood (kiloplatelets/mL).
level of serum creatinine in the blood (mg/dL).
level of serum sodium in the blood (mEq/L).
patient's sex (binary), Male, Female.
if the patient smokes or not (boolean), Yes, No.
follow-up period (days).
if the patient deceased during the follow-up period (boolean), Yes, No.
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.
"Heart Failure Prediction" in Kaggle https://www.kaggle.com/andrewmvd/heart-failure-clinical-data, License : CC BY 4.0
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
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