Mentify

• What it is:
  • Engineered a disease prediction system, utilizing algorithms like SVM and Logistic Regression for accurate assessments of diabetes, Parkinson's, and heart disease using a open source databases.
  • Achieved an average accuracy of 87% across models and diseases, demonstrating the effectiveness of the prediction system.
  • Integrated the system into a user-friendly application interface using Streamlit, allowing users and medical professionals to input information and predict diseases, enhancing early diagnosis and intervention strategies.
• Tech Stack:
• Python, SVM, Logistic Regression, Streamlit
• GitHub: Project Link