Trials / Unknown
UnknownNCT04584281
Artificial Intelligence (AI) in Cardiotocography (CTG) Interpretation
Introduction of Artificial Intelligence (AI) and Machine Learning in Cardiotocography (CTG) Interpretation to Improve Clinical Use
- Status
- Unknown
- Phase
- —
- Study type
- Observational
- Enrollment
- 15,000 (estimated)
- Sponsor
- Insel Gruppe AG, University Hospital Bern · Academic / Other
- Sex
- Female
- Age
- 18 Years
- Healthy volunteers
- Accepted
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.
Conditions
Timeline
- Start date
- 2020-10-01
- Primary completion
- 2021-06-01
- Completion
- 2021-06-01
- First posted
- 2020-10-12
- Last updated
- 2020-10-12
Locations
1 site across 1 country: Switzerland
Source: ClinicalTrials.gov record NCT04584281. Inclusion in this directory is not an endorsement.