Demonstration example for COVID-19 diagnosis based on routine blood tests
Problem description
The application of machine learning and artificial intelligence methods and algorithms in medical diagnostics is rapidly developing.
This example demonstrates a demo application for COVID-19 diagnosing based on routine blood tests.
Currently, the RT-PCR test is the gold standard for Covid-19 diagnosis. But this test has disadvantages, including high cost per test, long turnaround time for the test, people may have a positive test for up to 90 days after an infection has ended and the risk transmission has passed, and it requires special lab equipment and qualified personnel.
This example is an element of a multi-stage study on developing a decision support system in medical diagnosis.
This example demonstrates the opportunity for COVID-19 diagnosis based on routine blood tests.
What is shown in the example?
The demo application evaluates COVID-19 diagnosing and the risk of this evaluation based on blood tests for women in depending on Age, Hematocrit (HMCR), Hemoglobin (HMGL), Red Blood Cells (RBC), White Blood Cells (WBC), Platelets (PLAT), Mean platelet volume (MPV), Mean corpuscular volume (MCV), Mean corpuscular hemoglobin concentration (MCHC), Mean corpuscular hemoglobin (MCH), Red cell distribution width (RDW), Monocytes (MO), Lymphocytes (LY), Eosinophiles (EO), Basophiles (BA), and Neutrophiles (NE).
This application also checks the correctness of the White Blood Cells formula.
Note
The example is for demonstration only, and the results obtained in this example are not for practical application.
The value of the example is in demonstrating the potential of machine learning methods in medical diagnostics if applied correctly.
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