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Artificial Intelligence (AI) in Cardiotocography (CTG) Interpretation

NCT04584281 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 15000

Last updated 2020-10-12

No results posted yet for this study

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

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

Sponsors & Collaborators

  • CSEM Centre Suisse d'Electronique et de Microtechnique SA - Recherche et Developpement

    collaborator INDUSTRY

  • Insel Gruppe AG, University Hospital Bern

    lead OTHER

Eligibility

Min Age
18 Years
Sex
FEMALE
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2020-10-31
Primary Completion
2021-06-30
Completion
2021-06-30

Countries

  • Switzerland

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04584281 on ClinicalTrials.gov