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Table 6 Feature importance ranking of logistic regression

From: A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data

Rank Feature description
1 Cumulative number of 30-day readmissions
2 Presence of acute respiratory failure ICD-9 code
3 Number of abnormal sodium level laboratory tests
4 Presence of pneumonia (organism unspecified) ICD-9 code
5 Number of abnormal chloride level laboratory tests
6 Presence of acute kidney failure (unspecified) ICD-9 code
7 Presence of diabetes (with other specified manifestations) ICD-9 code
8 Presence of acute kidney failure (any) ICD-9 code
9 Presence of respiratory failure, WKF
10 Presence of disorders of fluid electrolyte and acid-base balance (any) ICD-9 code
11 Presence of disorders of fluid/electrolyte/acid-base, WKF
12 Number of abnormal albumin level laboratory tests
13 Presence of asphyxia and hypoxemia ICD-9 code
14 Presence of anemia of chronic illness ICD-9 code
15 Presence of hypokalemia ICD-9 code