Recently, large tech companies such as Google and Facebook have come under scrutiny for taking, storing, and selling data to third party companies with little to no involvement with the user in the data management process. The issue of data potentially getting into the hands of people who users are not comfortable with is especially paramount in the context of sensitive medical records. The more companies that know a users' vulnerabilities and insecurities, the greater the risk for exploitation. In an ideal world, medical information is kept between the patient and his/her doctor. This philosophy was used to design LebN and develop its privacy first implementation.

What it does

LebN takes in user medical data, such as physical symptoms, and compares it with open source medical databases on the user's and generates a personalized medical profile. This profile is stored locally on the user's device and gives personalized health advice catered to the user's individual requirements.

How we built it

The backend was built heavily with Firebase- we needed a way to privately store information on people's devices, while dealing with multiple profiles. The front end was built with a combination of bootstrap studio and dreamweaver, building upon a lot of CSS, JavaScript, and HTML elements. We later opted for a simpler vanilla javascript framework to suit the backend.

Challenges we ran into

When creating the front-end for LebN, the preexisting templates had a very strong integration between the CSS and Javascript, which essentially made it pretty much impossible to customize the front-end to interface with the back-end was being developed concurrently.

Accomplishments that we're proud of

It was the first hackathon ever for one of our members, and it provided a lot of opportunities to apply skills we learned in class to a real-world problem. We learned how to work between bootstrap studio & adobe dreamweaver- and while we weren't able to showcase our neat front-end like planned, we now know how to create beautiful, feature-rich, webpages within a few keystrokes.

What We learned

When developing a web app, one should not focus on making a nice front end without checking in with the back end developer. Looking back, it probably wasn't a good idea to develop the front and back-end independently, and working backwards for compatibility.

What's next for LebN

There is always room for improvement, and for LebN, that comes in the form of more sophisticated algorithms in correlating public health data to users' experiences. Additionally, there could be potential for the implementation of machine learning supported by a web crawler which updates LebN with cutting edge medical knowledge, further improving the potential of the app.

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