Automated discovery of positive and negative knowledge in clinical databases: A rule-induction method based on rough-set models that more closely represents medical experts' reasoning

IEEE Engineering in Medicine and Biology Magazine

Volumn 19, Issue 4, 2000, Pages 56-62

  Tsumoto, Shusaku ^a,b,c  

^a SHIMANE UNIVERSITY   (Japan)

^b Tokyo Institute of Technology ^*  (Japan)

^c TOKYO INSTITUTE OF TECHNOLOGY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATED KNOWLEDGE DISCOVERY; MEDICAL REASONING; ROUGH SET MODELS; RULE INDUCTION METHODS;

ALGORITHMS; DATABASE SYSTEMS; KNOWLEDGE REPRESENTATION; MATHEMATICAL MODELS; MEDICAL COMPUTING; PROBABILISTIC LOGICS; SET THEORY; THEOREM PROVING;

KNOWLEDGE ACQUISITION;

ACCURACY; ALGORITHM; COMPUTER ASSISTED DIAGNOSIS; DATA BASE; MATHEMATICAL ANALYSIS; MEDICAL TECHNOLOGY; REVIEW; SCIENCE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOMEDICAL ENGINEERING; CEREBROVASCULAR DISORDERS; DATABASES, FACTUAL; DIAGNOSIS, COMPUTER-ASSISTED; EXPERT SYSTEMS; HEADACHE; HUMANS; MENINGITIS; MODELS, STATISTICAL; MODELS, THEORETICAL;

EID: 0034234307     PISSN: 07395175     EISSN: None     Source Type: Journal    
DOI: 10.1109/51.853482     Document Type: Review

References (15)

1. Michalski RS, Mozetic I, Hong J, and Lavrac N: The multi-purpose incremental learning system AQ15 and its testing application to three medical domains. Proc 5th Nat Conf Artificial Intelligence, 1986, pp. 1041-1045.
2. Pawlak Z: Rough Sets. Dordrecht: Kluwer, 1991.
3. Quinlan JR: C4.5 - Programs for machine learning. Palo Alto, CA: Morgan Kaufmann, 1993.
4. Tsumoto S and Tanaka H: Automated discovery of medical expert system rules from clinical databases based on rough sets. In: Proc 2nd Int Conf Knowledge Discovery and Data Mining, 1996, pp. 63-69.
5. Tsumoto S: Modelling medical diagnostic rules based on rough sets. In: Polkowski L and Skowron A (Eds): Rough Sets and Current Trends in Computing (Lecture Notes in Artificial Intelligence). Heidelberg, Germany: Springer-Verlag, pp. 475-489, 1998.
6. Skowron, A and Grzymala-Busse J: From rough set theory to evidence theory. In: Yager R, Fedrizzi M. and Kacprzyk J (Eds.) Advances in the Dempsler-Shafer Theory of Evidence. New York: Wiley, pp. 193-236, 1994.
7. Shavlik JW and Dietterich TG (Eds): Readings in Machine Learning. Palo Alto, CA: Morgan Kaufmann, 1990.
8. Rissanen J: Stochastic Complexity in Statistical Inquiry. Singapore: World Scientific, 1989.
9. Ziarko W: Variable precision rough set model. J Comp and Syst Sci 46: 39-59, 1993.
10. Pawlak Z: Rough modus ponens. In: Proc Int Conf Information Processing and Management of Uncertainty in Knowledge-Based Systems, Paris, 1998, pp. 1162-1166.
11. Adams RD and Victor M: Principles of Neurology. 5th Ed. New York: McGraw-Hill, 1993.
12. Buchnan BG and Shortliffe EH (Eds): Rule-Based Expert Systems. Reading, MA: Addison-Wesley, 1984.
13. Tsumoto S: Automated extraction of medical expert system rules from clinical databases based on rough set theory. J Informat Sci 112: 67-84, 1998.
14. Matsumura Y, Matsunaga T, Hata Y, Kimura M, and Matsumura H: Consultation system for diagnoses of headache and facial pain: RHINOS. Medical Informatics 11: 145-157, 1988.
15. Matsumura Y, Matsunaga T, Maeda Y, Tsumoto S, Matsumura H, and Kimura M: Consultation system for diagnosis of headache and facial pain: "RHINOS." In: Proc Logic Program Conferences, 1985, pp. 287-298.