IDECOVID19

IDECOVID19 is a practical application that implements machine-learning algorithms for the identification of high-risk COVID-19 patients.
56 Downloads
Updated 10 Feb 2021

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This software can identify whether a given patient is more likely to survive than to die, or vice-versa. The interactive graphic user interface makes IDECOVID19 friendly and easy to use. This technology enables rapid identification of high-risk patients at four different treatment stages:

Stage 1. Patients who arrive at the Emergency department (or at the triage process) seeking medical attention for the first time.
Stage 2. Patients who as part of their evaluation already have a known COVID-19 status and may already have developed COVID-19-related pneumonia.
Stage 3. Patients for whom a decision has been reached as to whether admit into a hospital or send back home.
Stage 4. Patients who in addition to being hospitalized, have either been intubated or admitted into an intensive care unit.

How to install:

Option 1:
1. Download the file “IDECOVID19.mlappinstall”
2. Start MATLAB software
3. Go to “APPS” tab
4. Click “Install App”
5. Specify the folder in which you have the file “IDECOVID19.mlappinstall” and click “Open”. It displays a dialog box.
6. Click Install
7. IDECOVID19 app will be added to your apps

Option 2:
If you do not have MATLAB installed, you can run IDECOVID19 app by downloading the zip file from Matlab drive by going here: https://drive.matlab.com/sharing/99aeec2b-fa41-4fcf-8d81-e93a2ab71774
1. Unzip/Extract the archive containing the installer.
2. Start MyAppInstaller_web.exe
3. When the installer starts, it displays a dialog box. Read the information and then click Next to proceed with the installation. (To run IDECOVID19 app, the installer will verify that MATLAB Runtime is installed. If not, the installer can download and install it. To do this, you will need administrator rights.)
4. Click Finish to exit the installer. It will create an icon on the desktop.
5. Double-click to execute the IDECOVID19 app

Cite As

Mario A. Quiroz-Juárez, Armando Torres-Gómez, Irma Hoyo-Ulloa, Roberto de J. León-Montiel and Alfred B. U'Ren (2021). IDECOVID19 Identification of high-risk COVID-19 patients (https://www.mathworks.com/matlabcentral/fileexchange/87202-idecovid19), MATLAB Central File Exchange. Retrieved February 10, 2021.

MATLAB Release Compatibility
Created with R2019a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.0.1

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1.0.0