Application of Machine Learning Based Approaches in Emergency Department to Support Clinical Decision Managing SARS-CoV-2 Infected Patients

University of L'Aquila

Status: Unknown

Conditions: Covid19

Study type: Observational

Funder types: Other

Identifiers

NCT04825301

prot. N. 28958

Details and patient eligibility

About

The aim of the study is to develop a prognostic prediction model based on machine learning algorithms in patients affected by coronavirus disease 2019 (COVID-19), the prediction model will be capable to recognize patient with favorable prognosis or patient with poor prognosis by intelligent systems data analysis.

Enrollment: 779 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• patients aged over 18 positive for COVID-19 by polymerase chain reaction assay for rhino-pharyngeal swab

Exclusion criteria

• Under 18 aged

Trial design

779 participants in 2 patient groups

training cohort

Description:

data collection

validation cohort

Description:

data collection