Sugar slay: a gamified decision support ecosystem for type 1 diabetes
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By
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Sundararaman Rengarajan
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Nicholas Abrams
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Aspen Tabar
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Hariharan Sundaram
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Kavya Pratap Singh
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Leanne Chukoskie
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June 17, 2026
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Clinical Scorecard: Gamified Decision Support System for Managing Type 1 Diabetes
At a Glance
| Category | Detail |
|---|
| Condition | |
| Key Mechanisms | Integration of continuous glucose monitoring (CGM) and wearable device data with machine learning for personalized predictions. |
| Target Population | |
| Care Setting | |
Key Highlights
- Development of Sugar Slay ecosystem for T1D management.
- Utilization of Seq2Seq BiLSTM for blood glucose trend forecasting.
- Support for caregivers through Sugar Slay Care companion app.
Guideline-Based Recommendations
Diagnosis
- Continuous monitoring of blood glucose levels is essential.
Management
- Integration of physiological data from CGM and wearable devices.
Monitoring & Follow-up
- Regular assessment of glucose variability and related health metrics.
Risks
- Potential for cognitive overload in interpreting data.
Patient & Prescribing Data
Adolescents and young adults with Type 1 Diabetes.
Need for advanced decision support tools to optimize glycemic control.
Clinical Best Practices
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