Ask Indegene (Beta)
Hello, how can I help you today?
You may type your question or choose from the options below:
Thank you!
We'll be in touch. In the meantime, feel free to keep exploring!
#PractitionerLevelConfidence
Indegene Helps Predict the Early Diagnosis of Invasive GBS in Patients
Challenges
No systematic approach to detect invasive GBS infections in adults
Manual review of medical records delayed the process of reporting the invasive status of the disease in patients
The Solution
We built a descriptive and predictive analytical framework to identify patients with invasive GBS long before symptoms appear, avoiding hospitalization and future complexities. We leveraged real-world data to mine patient-level insights from hospitals, including clinical and pathologic findings. Using machine learning models, we automated the identification of key drivers contributing to the invasive properties of GBS, resulting in a faster diagnosis.
Outcomes
Through our predictive model, the customer identified invasive patterns in patients with GBS before the onset of symptoms. High vitals, such as the patient temperature at the time of hospitalization, and lab values, such as aspartate aminotransferase, albumin, and more, were identified as key predictors that helped in determining the invasive status of the infection.
0%
Accuracy in early detection of invasive GBS
0
Clinical features supporting the prediction
0
Machine learning modules tested
Let's Partner to Commercialize with Confidence
