Check out our prototype: https://prognosis-ai.onrender.com Check out our github repo of the website: https://github.com/Adam-Warlock09/Prognosis-AI
PROGNOSIS AI is an advanced machine learning-powered application designed to assess an individual's risk level for susceptibility to various diseases. By analyzing basic medical information provided by the user, the system predicts the likelihood of conditions such as:
- Diabetes
- Heart Diseases
- Lung Cancer
- Breast Cancer
- Anemia
- Asthma
With an average model accuracy of 90.5%, PROGNOSIS AI strives to offer reliable insights to assist in early detection and prevention.
Key Features
- Disease Risk Assessment: Predicts risk levels for multiple diseases using advanced algorithms.
- User-Friendly Input: Requires basic medical information to deliver accurate results.
- High Accuracy: Our models are rigorously trained, achieving an impressive average accuracy of 90.5%.
Machine Learning Algorithms We leverage a variety of machine learning techniques to ensure robust and accurate predictions, including:
- Decision Trees : For interpretable and rule-based predictions.
- Random Forests: To improve accuracy and reduce overfitting.
- Linear Regression: For modeling relationships between features and outcomes.
- Extreme Gradient Boosting (XGBoost): For high-performance and efficient modeling.
- User Input: The user provides essential medical details.
- Processing: The data is processed through our trained machine learning models.
- Prediction: Risk levels for various diseases are calculated and displayed.
Aric Maji Akshat Banzal Atul Boyal
Our models have been rigorously evaluated and optimized, resulting in an average accuracy of 90.78% across all supported conditions. This ensures reliable and actionable insights for users.