Inspiration:

Coronary Artery Disease (CAD) is the most common heart disease in the world. According to the CDC, heart disease is the leading cause of death globally, causing approximately 17.9 million deaths, which accounts for 32% of all global deaths annually. It is these facts that motivated our teams shared desire to stimulate life-savingly early detection software of CAD to help as many people as possible as well as to spread awareness about CAD.

How we built it:

The first thing we did is create our machine learning model. In order to do this, we first got a Kaggle data set which needed to be cleaned and edited. After that we created a model using Random Forest Classifier which allowed our model to reach prediction rates of 89% (these rates are acceptable in real world medical practices). Secondly, we created a front-end using HTML and CSS. While making these we used a form tag to input questions for the user to answer which were designed to be the exact same questions the machine learning model asked so we can connect both of them later on. Lastly, we created a backend which grabbed our ML model and then requested a form for our users input to than be sent to our model to get our prediction.

Challenges we ran into:

One of the many challenges we ran into was the understanding of backend development. None of us knew anything about it, so we had to learn everything from scratch in order to connect all the code together. Another challenge we ran into was working as a team. This was everyone's first time being a part of a group, and everyone knew different things. So, it was our responsibility to go past our comfort levels and overcome the challenge of facing new problems for the better cause of finishing this project.

Accomplishments that we're proud of:

We are proud of everything we have learned. Walking in here, some of knew very little. However, being faced with such a big challenge also means walking away with a big reward. We are proud of the knowledge we have gained as well has the opportunity to be a part of this event

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