Diabetes is a chronic medical condition characterized by high blood sugar levels. It occurs when the body doesn't produce enough insulin. According to International Diabetes Federation(IDF), in 2021, approximately 463 million adults were living with diabetes worldwide. This number is expected to rise to 700 million by 2045 if the current trend continues.
Parkinson's disease is a neurodegenerative disorder that affects movement control. The loss of neurons leads to a shortage of dopamine, a chemical messenger responsible for transmitting signals that coordinate movement. There is no cure available for this disease, but various treatment options are available to manage symptoms and improve quality of life.
Thus preventing Diabetes and Parkinson's disease has become more than necessary. Good Machine Learning systems for predicting these diseases can improve the entire research and prevention process. A robust system can be developed in the near future, making sure that more people can live healthy lives.
The Repository contains a disease prediction model based on the SVM algorithm. The model is trained on a dataset obtained from Kaggle. It can be used to predict the likelihood of a person having a particular disease based on their health report parameters. This model predicts Diabetes and Parkinson's disease.
Make sure you have the following prerequisites installed :
- Python 3.7
- Numpy
- Pandas
- Scikit-learn
The algorithm explored in the code is Support Vector Machine. It is a supervised machine-learning algorithm that is widely used for classification tasks. SVMs are particularly effective when working with complex datasets that have a clear margin of separation between different classes.
Accuracy score and F1 score are used for evaluating the accuracy of the model.
The prediction model in this repository is intended for informational purposes only and should not be considered as a substitute for diagnosis.