A health management application that analyzes users’ medical histories (comorbidities) and epigenetic data (DNA methylation) to predict their risk of developing specific diseases, such as ovarian cancer or cervical cancer.
Comorbidity-Based Prediction, which leverages users' historical medical data, is the foundational layer of our risk assessment model.
Upon launching the app for the first time, users are guided to input basic metrics, including height, weight, gender, and age. Note: We prioritize user privacy; no sensitive personally identifiable information (such as ID numbers) is collected.
Subsequently, users can select their pre-existing conditions from a comprehensive medical history list. Once the profile is set up, the main dashboard displays a personalized risk assessment for various diseases (e.g., Cervical Cancer, Colorectal Cancer). These insights are visualized through dynamic statistical charts and detailed data analysis.
- 🔒 Privacy Focused: The app does not collect sensitive personal data (e.g., National ID numbers).
- 📝 Medical History Tracking: Users can easily check off pre-existing conditions from a built-in disease list.
- 📊 Personalized Risk Assessment: The system calculates and displays risk levels for specific diseases (such as Cervical Cancer and Colorectal Cancer) based on user inputs.
- 📈 Data Visualization: The home dashboard presents risk data through intuitive statistical charts and graphs.
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n addition to manually selecting pre-existing conditions, users can import their National Health Record (NHR/health bank) data. This allows the system to automatically extract their medical history (comorbidities) for a seamless, one-click setup, instantly generating Comorbidity-Based Risk Assessments. A detailed tutorial is provided on the import page to guide users through the upload process.
Privacy Note: The app strictly processes disease history records only. We do not store or process any other personal information, ensuring complete data privacy and security.
- 📥 Health Record Import: Users can import their National Health Record (Health Bank) to automatically load their medical history and generate risk profiles.
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In addition to leveraging Comorbidity Data for risk prediction, this application also supports disease-risk evaluation using gene-level methylation markers (methylation targets).
Because methylation information provides a finer scale of epigenetic and biological features (biomarkers), its predictive accuracy is generally higher than estimates derived solely from Comorbidity Data. The resulting methylation-based risk profiles are also visualized through charts for easier interpretation.
- 🧬 Methylation-Based Prediction: Advanced disease-risk estimation using gene-level methylation markers, offering higher predictive precision than Comorbidity-only models.
- 📈 Data Visualization: Methylation risk results are displayed through boxplots and a color-scaled bar for clear visual interpretation.