An Empirical Model for Thyroid Disease Diagnosis Using Data Mining Techniques

  • Umar SidiqEmail author
  • Syed Mutahar Aaqib
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 39)


Utilization of data mining in healthcare sectors showing great role in effectiveness of treatment, healthcare administration, finding of fraud and abuse and customer relationship management but besides that it is also used for diagnosis of diseases. In this work, our focus is on diagnosis of thyroid diseases by using three classification models like K-Nearest Neighbor (K-NN), Decision Tree and Naïve bayes based on certain clinical thyroid attributes like Age, Gender, TSH, T3 and T4. The entire research work is to be conducted with RapidMiner version 8.1, an open source tool under Windows 10 environment. The Experimental study shows that decision tree outperformed over other models.


Thyroid disease K-nearest neighbor Decision tree Naïve Bayes 



There is no conflict of interest. We used our own data.


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer Science and System StudiesMewar UniversityChittorgarhIndia
  2. 2.Department of Computer ScienceAmar Singh CollegeSrinagarIndia

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