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Prioritizing Patients with Predicted Heart Disease Result with ML.NET

As the Amatis family, we touch the lives of thousands people every day with the applications and devices we have developed in the field of health, as developers we are happy to be involved in these projects.

Especially when subject comes to human life, the responsibility of the projects increase more. We always try to do better and make life easier to help more people with this sense of responsibility. This week, I will tell you about a model that we have applied similar in our projects.

First of all, I want to talk about the project we developed: Cardiologists analyze the patients information from the cloud-based ECG (electrocardiogram) devices and applications we have developed and create a report. The important point here is that the patients are analyzed according to their urgency. Previously, urgency was communicated by hospitals and this is how it was prioritized.

However, with the model we developed, prioritization is made by passing the patient's ECG and other health information through a model before the patient details come to the analysts. It is examined whether the patient has a critical condition and patients with critical condition are prioritized.

There is an application developed with ML.NET on Github which we also apply similarly. Heart disease is predicted using the model created by UCI Heart disease and if we have a patient with heart disease in the sample data, this is stated. We use a similar model of this model to prioritize our patients for our cloud-based analysis application.


You can find the relevant github repository here: Heart Disease Prediction

In addition, you can find many good examples to give you an idea in your ML projects, from this link: ML.NET Samples


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