Artificial Intelligence (AI) in Cardiotocography (CTG) Interpretation
October 5, 2020 updated by: University Hospital Inselspital, Berne
Introduction of Artificial Intelligence (AI) and Machine Learning in Cardiotocography (CTG) Interpretation to Improve Clinical Use
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.
Study Overview
Status
Unknown
Study Type
Observational
Enrollment (Anticipated)
15000
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Locations
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-
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Bern, Switzerland, 3010
- Recruiting
- Frauenklinik Inselspital Bern
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Contact:
- Anda I Radan, Dr. med.
- Phone Number: 0316321010 0316321010
- Email: anda-petronela.radan@insel.ch
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Contact:
- Karin I Strahm, Dr. med.
- Phone Number: 0316321010 0316321010
- Email: karin.strahm@insel.ch
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Principal Investigator:
- Daniel I Surbek, Prof. Dr. med
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Sub-Investigator:
- Anda I Radan, Dr. med.
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Sub-Investigator:
- Karin I Strahm, Dr. med.
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Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
18 years and older (Adult, Older Adult)
Accepts Healthy Volunteers
No
Genders Eligible for Study
Female
Sampling Method
Non-Probability Sample
Study Population
Patients with singleton pregnancies and CTG-registrations during labour from 01.01.2006 to 31.12.2019
Description
Inclusion Criteria:
- CTG-registrations of patients with singleton pregnancies during labour from 01.01.2006 to 31.12.2019
- Gestational age ≥ 24+0 weeks
- Age ≥ 18 years
- Written informed consent
Exclusion Criteria:
- Documented refusal
- Multiple pregnancies
- CTG-registrations of planned caesarean sections
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
- Observational Models: Cohort
- Time Perspectives: Retrospective
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Time Frame |
|---|---|
|
Superior prediction of fetal morbidity through the self-learning CDS system than if performed by obstetricians alone, especially in regards to specificity.
Time Frame: 3 months
|
3 months
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Anticipated)
October 1, 2020
Primary Completion (Anticipated)
June 1, 2021
Study Completion (Anticipated)
June 1, 2021
Study Registration Dates
First Submitted
October 5, 2020
First Submitted That Met QC Criteria
October 5, 2020
First Posted (Actual)
October 12, 2020
Study Record Updates
Last Update Posted (Actual)
October 12, 2020
Last Update Submitted That Met QC Criteria
October 5, 2020
Last Verified
October 1, 2020
More Information
Terms related to this study
Other Study ID Numbers
- 2020-00501
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.