With the advancement in data mining technologies, machine learning can be used to detect thyroid disorders at an early stage leading to early treatment and saving people’s lives. These techniques are being widely used for their ability to analyze large datasets and identify intrinsic relationships in the data better than human beings. So through this project, the aim is to work around the problem of thyroid disease identification and classification by developing a supervised learning model. With the help of this model, we will be able to understand the following:
- Predict whether an individual has a thyroid condition or is at risk of having one.
- Determine the type of thyroid condition, such as hyperthyroid or hypothyroid.
- Understand which gender is more prone to be diagnosed with this disorder.
- Python (statistical packages - NumPy, Pandas, Scikit-learn, Seaborn)
- Jupyter Notebook