Artificial Intelligence (AI) in Cardiotocography (CTG) Interpretation
The project at Inselspital Bern will develop a clinical decision support system that uses self‑learning AI to analyze cardiotocography traces from 10,000–15,000 maternity records. CSEM will design, develop, and validate multiple machine‑learning architectures to predict the optimal fetal extraction time during labor, providing a superhuman support tool for obstetricians. The system will be trained on existing clinical outcomes to improve decision‑making accuracy.
The project at Inselspital Bern will develop a clinical decision support system that uses self‑learning AI to analyze cardiotocography traces from 10,000–15,000 maternity records. CSEM will design, develop, and validate multiple machine‑learning architectures to predict the optimal fetal extraction time during labor, providing a superhuman support tool for obstetricians. The system will be trained on existing clinical outcomes to improve decision‑making accuracy.
It showcases Swiss expertise in AI‑driven healthcare solutions and supports the national agenda for AI in medicine.
Original source record. Open the original record to verify the underlying announcement.