UC-231 Symptom-Based Disease Prediction

This project focuses on leveraging large-scale data sets and advanced analytical techniques to predict the onset of diseases. By integrating data from medical records, genetic information, and environmental factors, the project aims to identify patterns and risk factors associated with various diseases. Machine learning algorithms and statistical models are employed to enhance the accuracy of predictions, enabling early diagnosis and personalized healthcare interventions. This approach improves patient outcomes and contributes to the efficiency and effectiveness of healthcare systems.