Skip to main content
MedPathMedPath Home
Clinical Trials/NCT04825301
NCT04825301
Unknown
Not Applicable

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

University of L'Aquila1 site in 1 country779 target enrollmentFebruary 27, 2020
Share to TwitterShare to FacebookShare to LinkedInShare to Reddit
ConditionsCovid19

Overview

Phase
Not Applicable
Intervention
Not specified
Conditions
Covid19
Sponsor
University of L'Aquila
Enrollment
779
Locations
1
Primary Endpoint
COVID-19 clinical course
Last Updated
4 years ago
OverviewInvestigatorsEligibility CriteriaOutcomesSitesSimilar Trials

Overview

Brief Summary

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.

Registry
clinicaltrials.gov
Start Date
February 27, 2020
End Date
April 30, 2022
Last Updated
4 years ago
Study Type
Observational
Sex
All

Investigators

Responsible Party
Principal Investigator
Principal Investigator

Clara Balsano

Full Professor

University of L'Aquila

Eligibility Criteria

Inclusion Criteria

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

Exclusion Criteria

  • •Under 18 aged

Outcomes

Primary Outcomes

COVID-19 clinical course

Time Frame: 2 months

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.

Secondary Outcomes

  • Application of machine learning algorithms on data of patients affected by COVID-19(2 months)

Study Sites (1)

Loading locations...

Similar Trials

Completed
Not Applicable
Machine Learning Model to Predict Postoperative Respiratory FailureNoncardiac Surgery
NCT04527094Seoul National University Hospital22,250
Completed
Not Applicable
Evaluating the Risk of Postoperative Venous Thromboembolism in Cervical Cancer PatientsVenous Thromboembolism
NCT06556953Haike Lei1,174
Not yet recruiting
Not Applicable
Deep Learning Model Predicts Pathological Complete Response of Lung Cancer Following Neoadjuvant ImmunochemotherapyDeep Learning ModelPathological Complete ResponseNon-small Cell Lung CancerNeoadjuvant Chemoimmunotherapy
NCT06285058Wuhan Union Hospital, China1,000
Recruiting
Not Applicable
Development of Machine Learning Models for the Prediction of BMI and Complications After Bariatric Surgery (CABS-Study)Body WeightPost-Op ComplicationAnastomosis, LeakingHiatal HerniaGERDInternal HerniaMesenteric HerniaIntussusceptionDiabetes Mellitus, Type 2Sleep Apnea, Obstructive
NCT05710913Dr. Med Anas Taha10,000
Not yet recruiting
Not Applicable
Establishment of Clinical Prediction Model for Postoperative Symptomatic Spinal Epidural HematomaSpinal Epidural Hematoma
NCT06633848Peking University Third Hospital2,000