post-operative
OpenML dataset with id 43040
Author name not available (Why is that?)
Full work available at URL: https://api.openml.org/data/v1/download/22045762/post-operative.arff
Upload date: 11 June 2021
Dataset Characteristics
Number of features: 12 (numeric: 11, symbolic: 0 and in total binary: 0 )
Number of instances: 65,532
Number of instances with missing values: 0
Number of missing values: 0
Author: Sharon Summers Source: UCI - 1993 Please cite: UCI
Post-Operative Patient Data Set
The classification task of this database is to determine where patients in a postoperative recovery area should be sent to next. Because hypothermia is a significant concern after surgery (Woolery, L. et. al. 1991), the attributes correspond roughly to body temperature measurements.
Attribute information
1. L-CORE (patient's internal temperature in C):
high (> 37), mid (>= 36 and <= 37), low (< 36)
2. L-SURF (patient's surface temperature in C):
high (> 36.5), mid (>= 36.5 and <= 35), low (< 35)
3. L-O2 (oxygen saturation in %):
excellent (>= 98), good (>= 90 and < 98),
fair (>= 80 and < 90), poor (< 80)
4. L-BP (last measurement of blood pressure):
high (> 130/90), mid (<= 130/90 and >= 90/70), low (< 90/70)
5. SURF-STBL (stability of patient's surface temperature):
stable, mod-stable, unstable
6. CORE-STBL (stability of patient's core temperature)
stable, mod-stable, unstable
7. BP-STBL (stability of patient's blood pressure)
stable, mod-stable, unstable
8. COMFORT (patient's perceived comfort at discharge, measured as
an integer between 0 and 20)
9. decision ADM-DECS (discharge decision):
I (patient sent to Intensive Care Unit),
S (patient prepared to go home),
A (patient sent to general hospital floor)
This page was built for dataset: post-operative
