Commit Inicial

data/tanveer/post-operative/post-operative.names

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+1. Title: Postoperative Patient Data
+
+2. Source Information:
+   -- Creators: Sharon Summers, School of Nursing, University of Kansas
+                Medical Center, Kansas City, KS 66160
+                Linda Woolery, School of Nursing, University of Missouri,
+                Columbia, MO 65211
+   -- Donor:    Jerzy W. Grzymala-Busse (jerzy@cs.ukans.edu) (913)864-4488
+   -- Date:     June 1993
+
+3. Past Usage:
+   1. A. Budihardjo, J. Grzymala-Busse, L. Woolery (1991). Program LERS_LB 2.5
+      as a tool for knowledge acquisition in nursing, Proceedings of the 4th
+      Int. Conference on Industrial & Engineering Applications of AI & Expert
+      Systems, pp. 735-740.
+
+   2. L. Woolery, J. Grzymala-Busse, S. Summers, A. Budihardjo (1991). The use
+      of machine learning program LERS_LB 2.5 in knowledge acquisition for 
+      expert system development in nursing. Computers in Nursing 9, pp. 227-234.
+
+4. Relevant Information:
+      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.
+
+      Results:
+      -- LERS (LEM2): 48% accuracy
+
+5. Number of Instances: 90
+
+6. Number of Attributes: 9 including the decision (class attribute)
+
+7. 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)
+
+8. Missing Attribute Values:
+     Attribute 8 has 3 missing values
+
+9. Class Distribution:
+     I (2)
+     S (24)
+     A (64)
+
+
+
+