Inspiration

One Sunday morning when I was normally browsing the web, I came across this paper titled An interpretable mortality prediction model for COVID-19 patients published in nature.com which gave me the inspiration to build this tool.

Link to the paper: https://www.nature.com/articles/s42256-020-0180-7

Flowchart

flowchart

What it does

It displays the probability of COVID-19 infection with respect to the results of the Blood Test. Following are the parameters:-

  • Lactic dehydrogenase (LDH),
  • Lymphocyte, and
  • High-sensitivity C-reactive protein (hs-CRP)

How I built it

  1. Django [Back-end framework]
  2. Scikit-learn (to train the model)

Challenges I ran into

Gathering the data to compile the COVID Blood Test dataset.

What I learned

I learned the concept of how Tailwind CSS is based upon class-based CSS styling, and how blood test parameters can also be taken into account for finding whether a person is infected with COVID-19 or not.

What's next for CBT Analysis - COVID Blood Test Analysis

To gather more real-world data and improve the dataset.

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