Abstract
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.
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Sidiq, U., Aaqib, S.M. (2020). An Empirical Model for Thyroid Disease Diagnosis Using Data Mining Techniques. In: Karrupusamy, P., Chen, J., Shi, Y. (eds) Sustainable Communication Networks and Application. ICSCN 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 39. Springer, Cham. https://doi.org/10.1007/978-3-030-34515-0_61
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DOI: https://doi.org/10.1007/978-3-030-34515-0_61
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