Table 1 Patients characteristics with selected nominal attributes.
From: A machine learning model to classify aortic dissection patients in the early diagnosis phase
Attributes | No. Positive | % Positive | No. Negative | % Negative |
|---|---|---|---|---|
Gender | ||||
Male | 255 | 77.3% | 116 | 71.6% |
Female | 75 | 22.7% | 46 | 28.4% |
Marital Status | ||||
Unmarried | 8 | 2.4% | 4 | 2.5% |
Married | 314 | 95.2% | 157 | 96.9% |
Widowed | 6 | 1.8% | 1 | 0.6% |
Divorced | 2 | 0.6% | 0 | 0% |
Admission Approach | ||||
Emergency | 168 | 50.9% | 40 | 24.7% |
Outpatient | 159 | 48.2% | 120 | 74.1% |
Transferred-in | 3 | 0.9% | 2 | 1.2% |
