TOWARDS ARTIFICIAL NEURAL NETWORK MODEL TO DIAGNOSE THYROID PROBLEMS

Authors

  • Dr. V.Sarasvathi

Keywords:

Abstract

Medical diagnosis can be viewed as a pattern classification problem: based a set of input features the goal is to classify a patient as having a particular disorder or as not having it. Thyroid hormone problems are the most prevalent problems nowadays. In this paper an artificial neural network approach is developed using a back propagation algorithm in order to diagnose thyroid problems. It gets a number of factors as input and produces an output which gives the result of whether a person has the problem or is healthy. It is found that back propagation algorithm is proved to be having high sensitivity and specificity.

How to Cite

Dr. V.Sarasvathi. (2011). TOWARDS ARTIFICIAL NEURAL NETWORK MODEL TO DIAGNOSE THYROID PROBLEMS. Global Journal of Computer Science and Technology, 11(5), 53–56. Retrieved from https://computerresearch.org/index.php/computer/article/view/716

TOWARDS ARTIFICIAL NEURAL NETWORK MODEL TO DIAGNOSE THYROID PROBLEMS

Published

2011-03-15