Thyroid Disease Detection using Deep Learning

Thyroid disease (TD) is one of the most progressive endocrine disorders in the human population today. Prediction of the endocrine disease is a critical task in the field of clinical data analysis. Machine Learning (ML) has shown effective results in the decision making and predictions from the enormous data generated by healthcare domain. Various studies in the prediction of thyroid disease have given only a glimpse using machine learning algorithms. In this project we have proposed three models based on the primary dataset collected from 3772 patients.

Data Set Information:

From Garavan Institute

Documentation: as given by Ross Quinlan

6 databases from the Garavan Institute in Sydney, Australia

Approximately the following for each database:

• 2800 training (data) instances and 972 test instances
• Plenty of missing data
• 29 or so attributes, either Boolean or continuously-valued