According to healthline.org coronary artery disease is the most dangerous disease in the world killing over 8.8 million people, and increasing at rapid rates, almost 40% every 15 years. Coronary artery disease is becoming a serious issue and can affect many people as it is very common. Hence, I wanted to create a webapp that is able to use various forms of ML to detect if someone is suffering from this disease so they can take proper precautions and stay safe.
What it does
This webapp uses machine learning and a Random Forest Classifier to take in inputs from user data about their current conditions and blood reports, it then adds it in the model with over a 90% + confidence and outputs if a user suffers from the disease or not. It makes sure the prediction is right with a deep learning subsegment in the proejct that is able to analyze CT scans of arteries and detect if the artery suffers from the disease or not 99+% accuracy. The last part is the NLP page where we have got positive and informative trending latest news that the user can read and check out to learn more about coronary artery diseases.
How I built it
Challenges I ran into
One main challenge was getting the flask to populate and quickly give the data realtime. Due to the deep learning being trainged on over 70000 images it was hard to get a quick response as training took over 3-4 hours, hence to counteract this problem, I saved the model and imported that in the code
Accomplishments that I'm proud of
I am proud of a creating a fullstack application all by myself Best UI ive made so far Over 10000 lines First deep learning project as a beginner in coding Second NLP and ML project
What I learned
I learned how to use random forest classifiers in depth, webscrape data, learned more html and css commands, how to make flask work realtime, saving the model, etc.
What's next for Cardiac Care
I want to try and promote this in a doctor's office so the webapp can be used to help out and save others.