My neighbours, relatives seemed to be troubled with chest pain which did not give me a good feeling within me so we decided to build a predictor/recommender for the above problem.

What it does

It takes in certain parameters related to our heart and feeds it into a trained ML model and gives back the prediction whether a person is fit or not and does he/she needs to consult a doctor or no.

How we built it

We built it using Machine learning, Flask, Web Development.

Challenges we ran into

At first to understand the column variables of the data was quite tough and in the later stages we ran into an unusual problem with the API which was then hopefully fixed.

Accomplishments that we're proud of

We have successfully created a website for the society where they can provide with the data which is easily available to them and help people learn or prevent cardiac arrests with a pre-knowledge of it.

What we learned

We learned how to make a successful API where the ML model needs multiple inputs which was quite a thing. Moreover, hacking has always been useful in recovering the knowledge my team mates and I have, which is left in some places of our brain dormant as time passes by.

What's next for Diagnose it!

The next thing is to connect it with a live hardware tool like a iwatch kind of thing which develops real time graphs and can give an alarm to the person at the very moment!

Share this project: