WebMD and deciding when it is necessary to go to the hospital. We wanted to aggregate a lot of information in one place so that users don't have to spend so much time looking up information on the internet. We wanted something that was accessible to most of the population, especially those of lower socioeconomic background.
What it does
First the user is met with a body diagram where they can click on the section of their body that ails them. Upon clicking on that section, the user fills out a survey with the same questions an Emergency assistant would fill out. Then the app uses the inputs and runs it against a database of previous solutions and outcomes (went to the hospital, home remedy, no problem, etc.). We use a machine learning technique to make a decision with a high probability of accuracy and return the diagnosis to the user. Should the user need to visit the hospital, the app will provide a list of all the nearest hospitals with descriptions like distance and time to get there driving, walking, biking or transiting along with whether the hospital accepts Medicare and Medicaid. If the user does not need to go to the hospital, the app tells them a couple of home remedies.
How we built it
We built an iPhone app that with a sleek interface to display information generated from a flask generated api. In the backend we send the survey and results of the survey. The results of the survey are run through our ML model that we update using professional opinions. We query google's places and locations api as well and healthcare.gov's api of medicare and medicaid accepting locations to provide the best option for someone needing medical attention.
Challenges we ran into
Google's doesn't always have uniform api responses Being able to call the api on the front end app Getting good data for questions Choosing a model that can use the aggregated data to produce valid results Querying from many places on the internet to produce a simple but useful list for the user
Accomplishments that we're proud of
Solving all of the problems above! Coming up with a working model Making easy the process of finding a nearby hospital
What we learned
Flask How to make REST API How to get data from legitimate sources More about Healthcare and socioeconomic issues Being aware of the difficulty people of lower socioeconomic status have in accessing healthcare Poorly implemented solutions in healthcare
What's next for Doctor BJCZZZ
Expanding solutions for more parts of the body More in depth surveys Keeping track of user biometrics