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AI for Health - Heart Failure Detection

Developing a machine learning model to predict blood values from electrocardiograms as an indication of heart failure.

Helping heart failure prevention with machine learning

Cardiovascular diseases (CVDs) are the leading cause of death globally, taking an estimated 17.9 million lives each year. More than four out of five CVD deaths are due to heart attacks and strokes, and one third of these deaths occur prematurely in people under 70 years of age.” – World Health Organization

Taking a blood sample to measure indicators of heart failure is expensive. Recent research has shown that blood values indicating the risk of a heart failure can be predicted with electrocardiograms (ECGs) of patients. An electrocardiogram is a simple test that can be used to check your heart’s rhythm and electrical activity. AI can play a big role in revolutionizing patient treatment without driving up the costs.

Info session

Our challenge partners

GOAL: Predict blood values from electrocardiograms

In this Challenge we will be developing a machine learning model to predict the blood values as an indication of heart failure from an ECG, and if this could substitute for the costly and less widely available approach of having to take a blood sample to detect heart failure.

To achieve this goal, the project will be guided by an expert from the Catharina hospital and the FruitPunch AI for Health - Eindhoven chapter.  

Who are we looking for? 

Anyone with an interest in AI for Health can apply. We expect some experience with Python programming and an interest in machine learning. A background experience with Deep Learning models is preferred, but anyone with the right motivation and ‘proof’ of understanding of the concepts discussed in this proposal can sign up!

You can join as a contributor (~12 hours per week commitment for 10 weeks) or coach (2-4 hours per week, only for experienced ML professionals)

We’ll organize masterclasses on relevant topics during the challenge. 

Did you know

🥥  Cardiovascular diseases (CVDs) are the leading cause of death globally, taking an estimated 17.9 million lives each year. 

🍉  The most important behavioral risk factors for heart disease and stroke are unhealthy diet, physical inactivity, tobacco use, and harmful use of alcohol.

🍊  The number of patients with heart failure worldwide nearly doubled from 33.5 million in 1990 to 64.3 million in 2017

Application deadline

May 25, 2022
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Timeline

Application deadline: 25 May 2022 

Challenge kick-off: 27 May 2022

Midterm presentation:  22 June 2022

Final presentations: 13 July 2022

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