An Innovative System to Improve Maternal Birth Outcomesbroad
AI4BirthCare · Horizon Europe grant · 2026-09-01–2027-05-31
EC contribution
Total cost
Beneficiaries
About the data
Source: CORDIS (official EU open data), Horizon Europe. Framework HORIZON · call HORIZON-EIC-2026-AIC · scheme HORIZON-EIC · topic HORIZON-EIC-2026-AIC-02. CORDIS record →
Objective
Childbirth-related complications represent a major global health concern, significantly affecting maternal outcomes. Every year, at least 40 million women experience long-term complications caused by childbirth, underscoring the urgency of improved preventive strategies. In clinical practice, healthcare professionals must make decisions under time pressure while managing increasingly complex cases and diverse patient profiles, highlighting the need for advanced, evidence-based decision support tools.AI4BirthCare is a data-driven decision support system designed to predict childbirth-related injuries. By integrating patient-specific data collected during routine prenatal care, it delivers real-time risk assessments in the final weeks of pregnancy. Unlike traditional approaches, this solution combines biomechanical simulations with artificial intelligence (AI) to identify injury-prone regions and support optimized delivery strategies. The system is designed for seamless integration with existing hospital electronic health record systems through an intuitive interface.The primary objectives of AI4BirthCare are to inform obstetricians about patient-specific injury risks, identify likely pelvic injury areas, and predict delivery success. This approach aims to support more cautious delivery strategies, enable timely preventive actions, and guide targeted postpartum examinations, thereby improving maternal quality of life.Scientifically, the system represents a significant leap forward by integrating biomechanical modeling, machine learning (ML), and clinical data to enable more precise, patient-specific injury prediction than existing approaches. Societally, it has the potential to reduce preventable injuries, support early detection, strengthen obstetric decision-making, and lower the long-term economic burden of maternal morbidity. Overall, AI4BirthCare seeks to reduce preventable maternal injuries and improve long-term health outcomes for women on a global scale.
Beneficiaries (1)
| Organisation | Country | Role | EC contribution | SME |
|---|---|---|---|---|
| INEGI - INSTITUTO DE CIENCIA E INOVACAO EM ENGENHARIA MECANICA E ENGENHARIA INDUSTRIAL | PT | coordinator | €300,000 | Yes |
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