Thyroid Disease Detection Using ML

Thyroid Disease Detection Using ML

Gayatri Patil1, Sonam Shinde2, Swaliya Mulla3, Priyanka Kadam4 ,

1Student, 2Student, 3Student, 4Student,

Computer Science And Engineering Department,

Padmabhooshan Vasantraodada Patil Institute of Technology, Budhgaon, Maharashtra

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Abstract- The purpose of this paper is to identify the diagnosis of thyroid disease and to classify types of thyroid disease. There are two types of thyroid diseases namely Hyperthyroid and Hypothyroid. Hypothyroid is a common variation of thyroid disease. Various Machine Learning Algorithms are being used to identify thyroid disease. We have mainly used classification algorithms named Decision Tree (DT), Random Forest (RF) and , KNN - K-nearest neighbours .By observing the results, we could predict that our Trained Dataset provides approximately more than 90% accuracy for Random Forest classification algorithm. We  have attempted to reduce the number of disease detection parameters.