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Methods Inf Med 1997; 36(02): 160-162
DOI: 10.1055/s-0038-1634698
Original Article
Schattauer GmbH

Extraction of Rules for Tuberculosis Diagnosis Using an Artificial Neural Network

H. L. Viktor
1   Department of Informatics, University of Pretoria, South Africa
,
I. Cloete
2   Department of Computer Science, University of Stellenbosch, South Africa
,
N. Beyers
3   Department of Paediatrics and Child Health, University of Stellenbosch, South Africa
› Author Affiliations
Further Information

Publication History

Publication Date:
20 February 2018 (online)

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Abstract:

The treatment of tuberculosis (TB) is a major challenge throughout the world. The Western Cape Region of South Africa has the highest occurrence of TB in the world. Here, TB is increasing due to improperly managed treatment programmes and inadequate facilities. The development of rules to aid medical practitioners in the early and accurate diagnosis of tuberculosis should prove worthwhile. A method to extract such diagnostic rules from an artificial neural network is presented. These rules accurately represent the knowledge embedded in the “raw” TB data.

Keywords:

Knowledge Processing - Diagnosis in Medicine - Neural Networks - Data Interpretation
 

  • References

  • 1 Shavlik JW. Combining Symbolic and Neural Learning. Machine Learning 1994; 12: 321-31.
    PubMedGoogle Scholar
  • 2 Towell GG, Shavlik JW. Refining Symbolic Knowledge Using Neural Networks. Machine Learning 1994; 12: 321-31.
    PubMedGoogle Scholar
  • 3 Viktor HL, Engelbrecht AP, Cloete I. Reduction of Symbolic Rules from Artificial Neural Networks Using Sensitivity Analysis. IEEE ICNN; 1995. Perth, Australia.:
    Google Scholar
  • 4 Viktor HL, Cloete I. Extracting DNF Rules from Neural Networks. International Workshop on Applications of Neural Networks; Torremolinos, Spain: June 1995
    Google Scholar
  • 5 The South African Tuberculosis Control Program: Practical Guidelines. Department of Health; South Africa: 1996
    Google Scholar