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Title: Acute Inflammations
Abstract: The data was created by a medical expert as a data set to test
the expert system, which will perform the presumptive diagnosis of two
diseases of the urinary system.
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Data Set Characteristics: Multivariate
Attribute Characteristics: Categorical, Integer
Associated Tasks: Classification
Number of Instances: 120
Number of Attributes: 6
Missing Values? No
Area: Life
Date Donated: 2009-02-11
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Source:
Jacek Czerniak, Ph.D., Assistant Professor
Systems Research Institute
Polish Academy of Sciences
Laboratory of Intelligent Systems
ul. Newelska 6, Room 218
01-447 Warszawa, Poland
e-mail: jacek.czerniak 'at' ibspan.waw.pl or jczerniak 'at' ukw.edu.pl
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Data Set Information:
The main idea of this data set is to prepare the algorithm of the expert
system, which will perform the presumptive diagnosis of two diseases of
urinary system. It will be the example of diagnosing of the acute
inflammations of urinary bladder and acute nephritises. For better
understanding of the problem let us consider definitions of both
diseases given by medics. Acute inflammation of urinary bladder is
characterised by sudden occurrence of pains in the abdomen region and
the urination in form of constant urine pushing, micturition pains and
sometimes lack of urine keeping. Temperature of the body is rising,
however most often not above 38C. The excreted urine is turbid and
sometimes bloody. At proper treatment, symptoms decay usually within
several days. However, there is inclination to returns. At persons with
acute inflammation of urinary bladder, we should expect that the illness
will turn into protracted form.
Acute nephritis of renal pelvis origin occurs considerably more often at
women than at men. It begins with sudden fever, which reaches, and
sometimes exceeds 40C. The fever is accompanied by shivers and one- or
both-side lumbar pains, which are sometimes very strong. Symptoms of
acute inflammation of urinary bladder appear very often. Quite not
infrequently there are nausea and vomiting and spread pains of whole
abdomen.
The data was created by a medical expert as a data set to test the
expert system, which will perform the presumptive diagnosis of two
diseases of urinary system. The basis for rules detection was Rough Sets
Theory. Each instance represents an potential patient.
The data is in an ASCII file. Attributes are separated by TAB. Each line
of the data file starts with a digit which tells the temperature of patient.
-- Attribute lines:
For example, '35,9 no no yes yes yes yes no'
Where:
'35,9' Temperature of patient
'no' Occurrence of nausea
'no' Lumbar pain
'yes' Urine pushing (continuous need for urination)
'yes' Micturition pains
'yes' Burning of urethra, itch, swelling of urethra outlet
'yes' decision: Inflammation of urinary bladder
'no' decision: Nephritis of renal pelvis origin
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Attribute Information:
a1 Temperature of patient { 35C-42C }
a2 Occurrence of nausea { yes, no }
a3 Lumbar pain { yes, no }
a4 Urine pushing (continuous need for urination) { yes, no }
a5 Micturition pains { yes, no }
a6 Burning of urethra, itch, swelling of urethra outlet { yes, no }
d1 decision: Inflammation of urinary bladder { yes, no }
d2 decision: Nephritis of renal pelvis origin { yes, no }
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Relevant Papers:
J.Czerniak, H.Zarzycki, Application of rough sets in the presumptive
diagnosis of urinary system diseases, Artifical Inteligence and Security
in Computing Systems, ACS'2002 9th International Conference Proceedings,
Kluwer Academic Publishers,2003, pp. 41-51
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Citation Request:
Please cite:
J.Czerniak, H.Zarzycki, Application of rough sets in the presumptive
diagnosis of urinary system diseases, Artifical Inteligence and Security
in Computing Systems, ACS'2002 9th International Conference Proceedings,
Kluwer Academic Publishers,2003, pp. 41-51