Tuberculosis Disease Diagnosis Using Artificial Neural Networks


Er O., Temurtas F., Tanrikulu A. C.

JOURNAL OF MEDICAL SYSTEMS, cilt.34, sa.3, ss.299-302, 2010 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 34 Sayı: 3
  • Basım Tarihi: 2010
  • Doi Numarası: 10.1007/s10916-008-9241-x
  • Dergi Adı: JOURNAL OF MEDICAL SYSTEMS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.299-302
  • Yozgat Bozok Üniversitesi Adresli: Evet

Özet

Tuberculosis is an infectious disease, caused in most cases by microorganisms called Mycobacterium tuberculosis. Tuberculosis is a great problem in most low income countries; it is the single most frequent cause of death in individuals aged fifteen to forty-nine years. Tuberculosis is important health problem in Turkey also. In this study, a study on tuberculosis diagnosis was realized by using multilayer neural networks (MLNN). For this purpose, two different MLNN structures were used. One of the structures was the MLNN with one hidden layer and the other was the MLNN with two hidden layers. A general regression neural network (GRNN) was also performed to realize tuberculosis diagnosis for the comparison. Levenberg-Marquardt algorithms were used for the training of the multilayer neural networks. The results of the study were compared with the results of the pervious similar studies reported focusing on tuberculosis diseases diagnosis. The tuberculosis dataset were taken from a state hospital's database using patient's epicrisis reports.