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Machine learning

As you can see in the figure below, different illnesses and pathogens stimulate unique responses in the human immune system - and this is observable in Full Blood Count (FBC) data.

FBC test laser scatter plots
FBC test laser scatter plots of immune cells in a healthy person, a person infected with influenza, and a person infected with SARS-CoV-2.

We have developed sophisticated machine learning models which are trained using all the historical FBC data from a population. These models can then be used to detect anomalies in current FBC tests from the same population - a rise in the number of anomalous samples from unrelated people could be a warning sign that an outbreak of infectious disease has occurred.

You can think of the BloodCounts! solution as a tsunami-like warning system for infectious disease outbreaks which uses the human immune response measured by the FBC test.

The BloodCounts! workflow.
The BloodCounts! workflow.

A major advantage is that our method requires zero knowledge of the causative pathogen to work!

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