PulseGuard is an innovative mobile application in progress, designed for the early detection of heart diseases using advanced machine learning models. The app aims to provide users with accurate predictions about their heart health, enabling them to take proactive steps for better health management.
Early Detection of Heart Diseases: Utilizes machine learning algorithms to predict potential heart conditions based on user data.
- Real-time Data Analysis: The background model analyzes real-time health data input by the user, offering insights on heart health.
- Graphical Health Trends: Generates graphs from historical data to help visualize health patterns over time.
- Medical Record Management: Plan to store and manage medical records, including cardiograms, in the future.
- Pictorial Data Analysis: A feature to analyze cardiograms and other medical images for detecting potential risks.
- Machine Learning: The ML component is fully developed, using techniques like Random Forest and XGBoost, combined through a Voting Classifier for improved accuracy.
- Application Development: The frontend and integration are still in progress, with a focus on delivering a seamless user experience using Kotlin for Android.
https://drive.google.com/file/d/1w9hmyjL6phRGzkwM0ak7yVCb3lz6pdBp/view?usp=sharing
- Machine Learning: Python
- Frontend: Kotlin
- Backend: Tensorflow
https://drive.google.com/file/d/1p1XB89hbk694TkPrMfjcFaJOsasLh85b/view?usp=sharing