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Early Detection of Clinical Deterioration in Patients With COVID-19 Using Machine Learning

NCT04828915 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 1000

Last updated 2021-04-02

No results posted yet for this study

Summary

The aim of this study is to use artificial intelligence in the form of machine learning analysing vital signs as well as symptoms of patients suffering from Covid19 to identify predictors of disease progression and severe course of disease.

Conditions

  • Covid19

Interventions

OTHER

Machine learning

Machine learning on vital parameters, clinical symptoms and underlying diseases

OTHER

Machine based evaluation

Quantification of the prediction power and identification of the most relevant predictive parameters

Sponsors & Collaborators

  • Max-Planck-Institute Tuebingen

    collaborator OTHER

  • University Hospital Tuebingen

    lead OTHER

Principal Investigators

  • Bernhard Schoelkopf, PhD · Max-Planck-Institute, Tuebingen, Germany

  • Juergen Hetzel, MD · University Hospital of Tuebingen, Tuebingen, Germany

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-02-01
Primary Completion
2021-07-31
Completion
2021-12-31

Countries

  • Germany

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 NCT04828915 on ClinicalTrials.gov