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Medisen

This is a website that allows you to inquire about your disease from the comfort of your own home. Avoid waiting in line and taking a day off to see your doctor, as well as the chance of human error. The procedure is very simple - type in the symptoms and select the recommended options that best describe your case from the table, and our website will calculate which possible diseases might have by comparing your symptoms to the ones that characterize each of the diseases in our database.

Getting Started

To get started with the web app:

1. Clone this repository
2. Install the necessary dependencies: `npm install` and `pip install -r requirements.txt`
3. Start the Flask server: `python server.py`
4. Start the React app: `npm start`

Algorithms Explored

The following algorithms have been explored in code:

1. K-Nearest Neighbors (KNN)
2. Decision Tree
3. Random Forest
4. Scikit-learn

Dataset

The dataset for this problem used with the main.py script is downloaded from here:

https://github.com/rohitpatil03/Solving-for-India/blob/main/Backend/Converted_Data_model.csv

This dataset has 139 total rows, 138 of them being symptoms experienced by patiend.

Directory Structure

|_ Backend/
     |_ Converted_Data_model.csv
     |_ server.py [Providing the API to train machine]

|_ML_Model.ipynb[Testing]

Conclusion

The use of machine learning algorithms for disease prediction based on symptoms is quite promising and can be a cost-effective and efficient way to diagnose diseases. The results of this project demonstrate the effectiveness of machine learning algorithms in predicting diseases based on symptoms. An interactive interface can also help healthcare professionals to make better decisions and provide accurate diagnoses.

Disclaimer

If you have symptoms of a very serious disease we highly encourage you to physically visit a health institution. In case the website suggests a medicine that requires a prescription from a professional institution, please make sure you visit your doctor and get one.

Contributors

Rohit Patil - Frontend, Google Cloud Deployment
Nishant Thakre - Backend, ML model
Anuj Shrivastava - Dataset, Documentation, ML model
Bhaskar Pandey - UI/UX Design

License

This project is released under the MIT License.

Links

Visit our project using the url : http://34.131.193.196/
Documentation : https://docs.google.com/document/d/15Ne33VQ2wGcJzbnVTleqgkKNGwd83OErpZ1Yk0mvG8s/edit

Open for Feedback and Suggestions

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