Heart Failure Clinical Records
About
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.
A detailed description of the dataset can be found in the Dataset section of the following paper:
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
Subject Area
Health and Medicine
Instances
299
Features
12
Data Types
Multivariate
Tasks
Classification, Regression, Clustering
Feature Types
Integer, Continuous
Features
| Name | Role | Type | Units | Missing Values | Description |
|---|---|---|---|---|---|
| age | Feature | Integer | years | No | |
| anaemia | Feature | Binary | - | No | |
| creatinine_phosphokinase | Feature | Integer | mcg/L | No | |
| diabetes | Feature | Binary | - | No | |
| ejection_fraction | Feature | Integer | % | No | |
| high_blood_pressure | Feature | Binary | - | No | |
| platelets | Feature | Continuous | kiloplatelets/mL | No | |
| serum_creatinine | Feature | Continuous | mg/dL | No | |
| serum_sodium | Feature | Integer | mEq/L | No | |
| sex | Feature | Binary | - | No | |
| smoking | Feature | Binary | - | No | |
| time | Feature | Integer | days | No | |
| death_event | Target | Binary | - | No |
Introductory Paper
Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone
D. Chicco, Giuseppe Jurman. 2020.
BMC Medical Informatics and Decision Making