TOWARDS ARTIFICIAL NEURAL NETWORK MODEL TO DIAGNOSE THYROID PROBLEMS
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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.
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Published
2011-03-15
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Copyright (c) 2011 Authors and Global Journals Private Limited
This work is licensed under a Creative Commons Attribution 4.0 International License.