AI/ML Application in Hypoglycemia Risk Prediction for Diabetic Patients

A medical facility running a specialized care program for diabetic patients. The client’s goal was to implement a system capable of predicting hypoglycemia risk and automatically notifying patients about potential health threats.

Hypoglycemia poses one of the most serious risks for individuals with diabetes. Previously, monitoring hypoglycemia risk required intensive involvement from medical teams and was highly time-consuming.

The client needed a solution that would:

• Automatically analyze data from glucose meters, medication information, and patient-specific data.
• Predict the likelihood of hypoglycemia episodes.
• Send timely alerts to patients when a potential risk was identified.
• Reduce the need for constant patient monitoring by medical staff.

1. Predictive Model Design and Development
   We developed an AI/ML model that analyzed glucose level readings, medication usage, and individual patient data to assess the risk of hypoglycemia.
2. Notification System Implementation
   We built a notification mechanism that sends alerts to patients whenever the model detects an increased risk of hypoglycemia.
3. Validation and Optimization
   The model was thoroughly tested and achieved high performance metrics:

• Sensitivity: 88%
• Specificity: 85%

The system was customized to fit the needs of the healthcare facility and its patients.

The solution was very well received by both the medical team and patients enrolled in the care program. It enabled effective prediction of hypoglycemia risk and automated patient notifications.

As a result, patient safety significantly improved, along with their overall quality of life. The development process and collaboration with the client ran smoothly, with ongoing monitoring and knowledge-sharing from our team, which facilitated successful implementation and future use of the system.