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Clinical Trial Summary

The project leaders plan to create a clinical decision support (CDS) system by programming a self-learning software to analyze the cardiotocography (CTG) traces in the - already existing - database from the maternity department of the Inselspital Berne. The project leaders will process and analyze all clinical outcomes of the estimated 10000-15000 eligible patient records. CSEM will design, develop, and validate several AI architectures with the intend to create the CDS system. The AI would learn to assist on this task by training machine learning (ML) algorithms. The main purpose of the AI-CDS will be to determine the best fetal extraction moment during labor, based on a self-learning approach, as a "superhuman" support tool for obstetricians in decision making during labor.


Clinical Trial Description

n/a


Study Design


Related Conditions & MeSH terms

  • To Introduce Artificial Intelligence (AI) and Machine Learning in Cardiotocography (CTG) Interpretation to Improve Clinical Use

NCT number NCT04584281
Study type Observational
Source University Hospital Inselspital, Berne
Contact Anda Radan
Phone 0316321010
Email anda-petronela.radan@insel.ch
Status Recruiting
Phase
Start date October 2020
Completion date June 2021