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

University Hospital Tuebingen

Status: Unknown

Conditions: Covid19

Treatments: Other: Machine based evaluation; Other: Machine learning

Study type: Observational

Funder types: Other

Identifiers

NCT04828915

TEDDI

Details and patient eligibility

About

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.

Enrollment: 1,000 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Written informed consent
• Age >= 18 years
• Detection of SARS-CoV2 within the past 5 days

Exclusion criteria

• Inability to measure vital parameters and document symptoms

Trial design

1,000 participants in 2 patient groups

Training cohort

Description:

Randomly selection of 80% of the study population. The machine learning algorithm is trained on this dataset

Treatment:

Other: Machine learning

Validation cohort

Description:

Randomly selection of 20% of the study population. The machine learning algorithm which was trained on the basis of the training data cohort is validated on the validation cohort.

Treatment:

Other: Machine based evaluation