Diabetes analysis engine

Revolutionizing Diabetes Management through Advanced Data Analysis

1. Clinical Dashboard

Analysis:

• Purpose: Centralized platform for monitoring and managing patient data.
• Components:
  • Patient Overview: Summarized view of key health metrics for all patients.
  • Alerts and Notifications: Real-time alerts for critical patient conditions.
  • Patient Data Comparison: Compare data across different patients to identify common trends and anomalies.

User Manual:

1. Accessing the Dashboard:
   • Log in to the DaiBETES LIFE platform.
   • Navigate to the ‘Clinical Dashboard’ from the main menu.
2. Monitoring Patient Health:
   • View the ‘Patient Overview’ for a summary of key metrics.
   • Click on individual patients to see detailed health data.
3. Setting Alerts:
   • Customize alerts for critical conditions in the ‘Settings’ menu.

2. Patient Data Management

Analysis:

• Purpose: Comprehensive access to patient health records and metrics.
• Components:
  • Detailed Patient Profiles: Complete health history and current status.
  • CGM Data Analysis: In-depth analysis of continuous glucose monitoring data.
  • Insulin and Medication Logs: Track patient medication adherence and effectiveness.

User Manual:

1. Viewing Patient Profiles:
   • Navigate to the ‘Patients’ section.
   • Select a patient to view their detailed profile.
2. Analyzing CGM Data:
   • Access the ‘CGM Data’ tab in the patient profile.
   • Use the provided tools to analyze glucose trends and patterns.
3. Reviewing Medication Logs:
   • Go to the ‘Medication Logs’ tab.
   • Review the patient’s insulin and medication history.

3. Predictive Analytics

Analysis:

• Purpose: Advanced AI-driven predictive tools for proactive care.
• Components:
  • Glucose Trend Predictions: Forecast future glucose levels based on historical data.
  • Complication Risk Assessment: Predict the risk of diabetes-related complications.
  • Personalized Treatment Plans: Generate individualized treatment recommendations.

User Manual:

1. Using Predictive Tools:
   • Access the ‘Predictive Analytics’ section.
   • Select a patient and view the predicted glucose trends.
2. Assessing Risk:
   • Use the risk assessment tool to evaluate the likelihood of complications.
3. Generating Treatment Plans:
   • Enter patient-specific data to receive personalized treatment recommendations.

4. Interactive Visualization Tools

Analysis:

• Purpose: Dynamic and intuitive data visualization for better decision-making.
• Components:
  • Interactive Graphs and Charts: Visualize trends and patterns in patient data.
  • Time-Based Analysis: Analyze data over various time periods (daily, weekly, monthly).
  • Correlative Analysis: Identify correlations between different health metrics.

User Manual:

1. Viewing Visualizations:
   • Navigate to the ‘Visualization Tools’ section.
   • Select the type of chart or graph to view.
2. Customizing Time Frames:
   • Use the date range selector to customize the time frame for analysis.
3. Performing Correlative Analysis:
   • Select multiple metrics to compare and identify correlations.

5. Research and Development Tools

Analysis:

• Purpose: Tools for conducting and supporting diabetes research.
• Components:
  • Data Aggregation: Collect and analyze data from multiple patients.
  • Longitudinal Studies: Conduct studies on long-term trends and treatment outcomes.
  • Publication Support: Tools to assist in the preparation of research papers and studies.

User Manual:

1. Aggregating Data:
   • Access the ‘Research Tools’ section.
   • Use the data aggregation feature to collect data from selected patients.
2. **Conducting Studies

Transforming Diabetes Care Through AI-Powered Precision

Empower Your Health with DaiBETES Life