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"MediPredict" is a cutting-edge disease prediction tool utilizing machine learning techniques. It handles outliers and null values efficiently, ensuring accurate predictions. With models like SVM, Gaussian Naive Bayes, and Random Forest, it delivers reliable results, revolutionizing healthcare.

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Project Name: MediPredict

Description: MediPredict is an innovative machine learning project designed to revolutionize disease prediction in the healthcare domain. Leveraging advanced algorithms and techniques, it analyzes medical data to accurately predict various diseases. By handling outliers and null values intelligently, this project ensures robustness and reliability in its predictions. With models such as Support Vector Machines (SVM), Gaussian Naive Bayes, and Random Forest, it delivers high-performance results, empowering proactive and personalized medical care.

Key Features:

  • Accurate disease prediction using machine learning algorithms.
  • Intelligent handling of outliers and null values for robust predictions.
  • Utilizes models such as SVM, Gaussian Naive Bayes, and Random Forest for high-performance results.
  • Empowers proactive and personalized medical care.

How to Use:

  1. Clone the repository to your local machine.
  2. Install the required dependencies.
  3. Run the main script to execute disease prediction.
  4. Explore the predictions and insights provided by the models.

Contributing: Contributions are welcome! If you have ideas for improvement or want to add new features, feel free to open an issue or submit a pull request.

License: This project is licensed under the MIT License.

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"MediPredict" is a cutting-edge disease prediction tool utilizing machine learning techniques. It handles outliers and null values efficiently, ensuring accurate predictions. With models like SVM, Gaussian Naive Bayes, and Random Forest, it delivers reliable results, revolutionizing healthcare.

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