Muthuvijayalakshmi, M and Kumar, E and Ponnuraja, C (2018) Neural network based tuberculosis disease classification. International Journal of Scientific Research and Reviews, 7 (3). pp. 514-522. ISSN 2279–0543
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Abstract
Symptoms based Tuberculosis disease diagnosis is one of the challenging tasks in the medical field. So many techniques are availabe for classification of data such as Artificial Neural Network, Support vector machine and Genetic Algorithm. The objective of this paper is to construct a Multiplayer Feed Forward Neural Network model for the diagnosis of Tuberculosis. The trained network serves as a knowledge base of the system. The construction of the system is presented in this paper. This model correctly classifies 92.3%.
| Affiliation: | ICMR-National Institute for Research in Tuberculosis |
|---|---|
| Item Type: | Article |
| Uncontrolled Keywords: | Artificial Neural Network, Tuberculosis, Multiplayer Feed Forward Neural Netwrk. |
| Subjects: | Tuberculosis > Biostatistics |
| Divisions: | Statistics |
| Depositing User: | Dr. Rathinasabapati R |
| Date Deposited: | 28 Oct 2022 07:15 |
| Last Modified: | 28 Oct 2022 07:15 |
| URI: | http://eprints.nirt.res.in/id/eprint/1632 |
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