Being Diabetes Cautious

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Result (Negative)
Result (Positive Result)
Predict (Negative)

Inspiration

A lot of people in our family have diabetes, sometimes i wonder if i am prone to it and can that be predicted based on some medical details. I am pretty sure i'm not alone.

What it does

It basically takes a fe factor inputs and our machine learning model designed using python predicts your chances of having diabetes and recommends a few tips tailored based on the medical components entered.

How we built it

We build it by analyzing and implementing algorithms on a dataset and used recommenders conditions based on data calculated.

Challenges we ran into

NodeJs,Machine learning was a new concept for all of us and this is the first time we actually implemented it in a project

Accomplishments that we're proud of

We were finally able to get everything running in time and it predicts my diabetes status here.

What we learned

New technologies and the skill to network with people. It was an amazing experience.

What's next for Being Diabetes Cautious

We are planning to make this more efficient and bring it to our real life audience so that they can be careful and take precautions if prone to diabetes.

Built With

Submitted to

Created by

Mainly worked on the Prediction algorithm through Python and designed the UI for the Predictor.

Geetanjali Purohit
Majorly worked at designing and implementing the Prediction part through Python along with Designing the UI for the Predictor.

Ishita Gupta
I worked on the backend for this project, created the API for getting the result for the prediction.

Harsh Kumar