CovidResearchTrials by Shray Alag

CovidResearchTrials Covid 19 Research using Clinical Trials (Home Page)

Nil interventionWiki

Developed by Shray Alag
Clinical Trial MeSH HPO Drug Gene SNP Protein Mutation


Correlated Drug Terms (1)

Name (Synonyms) Correlation
drug3379 none, this study is observational Wiki 1.00

Correlated MeSH Terms (1)

Name (Synonyms) Correlation
D018352 Coronavirus Infections NIH 0.04

Correlated HPO Terms (0)

Name (Synonyms) Correlation

There is one clinical trial.

Clinical Trials

1 Artificial Intelligence-assisted Diagnosis and Prognostication in COVID-19 Using Electrocardiograms and Imaging

Coronavirus Disease 2019 (COVID-19) has been widespread worldwide since December 2019. It is highly contagious, and severe cases can lead to acute respiratory distress or multiple organ failure. On 11 March 2020, the WHO made the assessment that COVID-19 can be characterised as a pandemic. With the development of machine learning, deep learning based artificial intelligence (AI) technology has demonstrated tremendous success in the field of medical data analysis due to its capacity of extracting rich features from imaging and complex clinical datasets. In this study, we aim to use clinical data collected as part of routine clinical care (heart tracings, X-rays and CT scans) to train artificial intelligence and machine learning algorithms, to accurately predict the course of disease in patients with Covid-19 infection, using these datasets.

NCT04510441 Coronavirus Other: Nil intervention
MeSH:Coronavirus Infections

Primary Outcomes

Description: Accuracy with which computer based analysis (machine learning) can diagnose and/or prognosticate Covid-19 Number of Participants With COVID19 who died or survived following hospital admission

Measure: Accuracy of machine learning to be able to predict outcome of coronavirus (COVID-19) infection

Time: At the end of data analyses, approximately 1 year

Description: Number of participants who required invasive vs non-invasive ventilation vs ward-based care vs died

Measure: Accuracy of machine learning to be able to predict prognosis of coronavirus (COVID-19) infection

Time: At the end of data analyses, approximately 1 year

Secondary Outcomes

Description: Number of participants who had COVID19-related heart problems.

Measure: Accuracy of machine learning to be able to predict cardiac involvement of coronavirus (COVID-19) infection

Time: At the end of data analyses, approximately 1 year

Description: Number of participants that can be identified as having COVID19 using machine learning vs human or other clinical test or assessment

Measure: Accuracy of machine learning vs human assessment to diagnose coronavirus (COVID-19) infection

Time: At the end of data analyses, approximately 1 year

No related HPO nodes (Using clinical trials)