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Kidney Stone Detection Project

Overview

This project aims to predict the likelihood of kidney stone formation using machine learning models. The project leverages IBM Cloud services, including IBM Watson Studio and AutoAI, to build, train, and deploy the model. The deployed model is then integrated into a web application that takes user input, sends it to the deployed model endpoint, and displays the prediction.

Table of Contents

Features

  • Data preprocessing and analysis using IBM Watson Studio.
  • Automated model selection and training using IBM Watson AutoAI.
  • Deployment of the best model on IBM Cloud.
  • Web application for user interaction and prediction display.

Access

  • Project code can be accessed by GitHub Repo
  • Project can be used through the Gradio app App

Architecture

  1. Data Collection and Preprocessing: Data related to kidney stone formation is collected and preprocessed using IBM Watson Studio.
  2. Model Training: IBM Watson AutoAI is used to automatically train and select the best model based on the provided dataset.
  3. Model Deployment: The best model is deployed on IBM Cloud.
  4. Web Application: A web application is developed to take user input, send it to the deployed model endpoint, and display the prediction result.

IBM Cloud Services Used

  • IBM Watson Studio: For data preprocessing, analysis, and model training.
  • IBM Watson AutoAI: For automated model training and selection.
  • IBM Cloud: For deploying the best model and hosting the prediction endpoint.

Disclaimer

Kidney Stone Prediction App

Please note that this Kidney Stone Prediction App is designed solely for research and informational purposes. It is not intended to diagnose, treat, cure, or prevent any medical condition, including kidney stones. The predictions and suggestions provided by this app are based on research data and algorithms that are still in development.

Important:

  • The app's predictions should not be used as a substitute for professional medical advice, diagnosis, or treatment.
  • Always consult with a qualified healthcare provider before making any decisions regarding your health.
  • If you experience any symptoms or have concerns about your health, seek immediate medical attention.

The developers of this app make no guarantees regarding the accuracy or reliability of the predictions and assume no liability for any decisions made based on the information provided by this app.

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or suggestions.

License

This project is licensed under the MIT License. See the LICENSE file for more details.