Extraction of rules for tuberculosis diagnosis using an artificial neural network

Methods of Information in Medicine

Volumn 36, Issue 2, 1997, Pages 160-162

  Viktor, H L ^a   Cloete, I ^b   Beyers, N ^b  

^a UNIVERSITY OF PRETORIA   (South Africa)

^b STELLENBOSCH UNIVERSITY   (South Africa)

Author keywords

Data interpretation; Diagnosis in medicine; Knowledge processing; Neural networks

Indexed keywords

ARTIFICIAL NEURAL NETWORK; COMPUTER PROGRAM; COMPUTER SYSTEM; INFORMATION SCIENCE; INFORMATION SYSTEM; PRIORITY JOURNAL; REVIEW; TUBERCULOSIS;

EID: 0030754047     PISSN: 00261270     EISSN: None     Source Type: Journal    
DOI: 10.1055/s-0038-1634698     Document Type: Review

References (5)

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