source: orange/orange/doc/datasets/post-operative.htm @ 1760:9d4bb141fb0e

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data info file

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1<html>
2<head>
3<title>Postoperative Patient Data Base</title>
4</head>
5<body>
6<h1>Info on Postoperative Patient Data Base</h1>
7<pre>
8
91. Title: Postoperative Patient Data
10
112. Source Information:
12   -- Creators: Sharon Summers, School of Nursing, University of Kansas
13                Medical Center, Kansas City, KS 66160
14                Linda Woolery, School of Nursing, University of Missouri,
15                Columbia, MO 65211
16   -- Donor:    Jerzy W. Grzymala-Busse (jerzy@cs.ukans.edu) (913)864-4488
17   -- Date:     June 1993
18
193. Past Usage:
20   1. A. Budihardjo, J. Grzymala-Busse, L. Woolery (1991). Program LERS_LB 2.5
21      as a tool for knowledge acquisition in nursing, Proceedings of the 4th
22      Int. Conference on Industrial & Engineering Applications of AI & Expert
23      Systems, pp. 735-740.
24
25   2. L. Woolery, J. Grzymala-Busse, S. Summers, A. Budihardjo (1991). The use
26      of machine learning program LERS_LB 2.5 in knowledge acquisition for
27      expert system development in nursing. Computers in Nursing 9, pp. 227-234.
28
294. Relevant Information:
30      The classification task of this database is to determine where
31      patients in a postoperative recovery area should be sent to next. 
32      Because hypothermia is a significant concern after surgery
33      (Woolery, L. et. al. 1991), the attributes correspond roughly to body
34      temperature measurements.
35
36      Results:
37      -- LERS (LEM2): 48% accuracy
38
395. Number of Instances: 90
40
416. Number of Attributes: 9 including the decision (class attribute)
42
437. Attribute Information:
44     1. L-CORE (patient's internal temperature in C):
45              high (> 37), mid (>= 36 and <= 37), low (< 36)
46     2. L-SURF (patient's surface temperature in C):
47              high (> 36.5), mid (>= 36.5 and <= 35), low (< 35)
48     3. L-O2 (oxygen saturation in %):
49              excellent (>= 98), good (>= 90 and < 98),
50              fair (>= 80 and < 90), poor (< 80)
51     4. L-BP (last measurement of blood pressure):
52              high (> 130/90), mid (<= 130/90 and >= 90/70), low (< 90/70)
53     5. SURF-STBL (stability of patient's surface temperature):
54              stable, mod-stable, unstable
55     6. CORE-STBL (stability of patient's core temperature)
56              stable, mod-stable, unstable
57     7. BP-STBL (stability of patient's blood pressure)
58              stable, mod-stable, unstable
59     8. COMFORT (patient's perceived comfort at discharge, measured as
60              an integer between 0 and 20)
61     9. decision ADM-DECS (discharge decision):
62              I (patient sent to Intensive Care Unit),
63              S (patient prepared to go home),
64              A (patient sent to general hospital floor)
65
668. Missing Attribute Values:
67     Attribute 8 has 3 missing values
68
699. Class Distribution:
70     I (2)
71     S (24)
72     A (64)
73</pre>
74</body>
75</html>
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