🌐 Maternal Risk Decision Support: A Student-Led Innovation

Posted on May 8, 2025

Maternal Risk Decision Support: A Student-Led Innovation

We are proud to announce that our first-year midwifery students, Angela Lavntarakou and Eleni Samara, presented their research at the 10th Student Symposium on Research and Innovation hosted by Metropolitan College.

Our paper received the First Prize for Best Paper in the School of Health. 🏆 Many thanks to the School and the symposium organizers for recognizing our effort and promoting impactful research

Under my academic supervision, our team developed a web-based Maternal Risk Decision Support System, which is now publicly available:

👉 Try the Application

🧠 About the Project

Title: Analysis of Clinical Risk Thresholds During Pregnancy and Development of a Web-Based Decision Support Application

The application is based on statistical analysis of real-world data from the Maternal Health Risk Dataset (Ahmed et al., 2020, Springer). Importantly, it does not rely on fixed clinical rules, but rather on combinatorial statistical analysis of all relevant clinical variables, including:

Systolic Blood Pressure
Diastolic Blood Pressure
Blood Sugar (BS)
Heart Rate
Age

Through this multidimensional approach, the system classifies maternal risk into three levels:

🟥 High Surveillance
🟧 Medium Surveillance
🟩 Low Surveillance

⚠️ Disclaimer

This tool is intended strictly for educational and research purposes. It is not a diagnostic tool and must never replace medical advice. Always consult a qualified healthcare provider for medical concerns.

💡 Why It Matters

Provides interpretable, real-time risk classification
Supports midwifery education and primary care training
Offers an accessible alternative to black-box AI systems
Can be expanded with real-time data or integrated into IoT platforms

We invite educators, healthcare professionals, and researchers to explore the tool and reflect on the role of transparent, data-driven applications in maternal care.