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

University of L'Aquila779 enrolled

Overview

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.

Study Type

OBSERVATIONAL

Enrollment

779

Conditions

Covid19

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

Inclusion Criteria: * patients aged over 18 positive for COVID-19 by polymerase chain reaction assay for rhino-pharyngeal swab Exclusion Criteria: * Under 18 aged

Locations (1)

University of L'Aquila

L’Aquila, Italy

RECRUITING

Outcomes

Primary Outcomes

COVID-19 clinical course

Data about sex, age, symptoms start date, symptoms, comorbidity, vital parameters, hematochemical blood tests, therapy, oxygen support, radiology, clinical disease progression will be collected. The collected data will be analyzed through a machine learning based approach to predict the prognosis of patients affected by COVID-19.

Time frame: 2 months

Secondary Outcomes

Application of machine learning algorithms on data of patients affected by COVID-19

The collected data will be analyzed through a machine learning based approach to establish correlations between collected data and the prognosis of patients affected by COVID-19.

Time frame: 2 months

Data from ClinicalTrials.gov

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