Inspiration

Inspired by the idea of providing more accurate information about patients to hospitals and the development of precision medicine, we created this application as a form of aide towards hospitals and patients. We wanted to provide a way for doctors to have information and data about a specific patient. We also wanted to provide a way for analysis of individual patients to be made, to better decide medical treatment for a specific patient, and to base it on a patient's own analysis rather than an average. This is how we wanted to contribute towards precision medicine. Lastly, we desired to create a way for clients to easily set their own appointments easily with a simple website.

What it does

The project consists of two things: a hospital-side application and a client-side application. The hospital-side application is a desktop applications to allows doctors to look up patient information, see patient details, and discover patient analysis based on their history. The client-side application is a website that allows patients to easily create appointments, pay fees, and check for available treatments.

How we built it

We used Java to build the desktop application. The UI was created using the JavaFX libraries. For the website, it was built using HTML and we used Softheon's payment API for the "Pay the fees" section.

Challenges we ran into

We had trouble using a data set at first. Some issues came from downloading the data set itself. However, after gaining some assistance from the representatives at 1010Data, we managed to surpass some of the initial issues we faced when it came to the data set.

Accomplishments that we're proud of

We are proud of what we were able to do as a team within a short amount of time. It was a pleasure being able to work in a team who's own tasks ultimately lead to the development a final product. I was also proud of my ability to learn JavaFX and to create an application given my limited knowledge in Java.

What we learned

We learned about handling data sets and how that data can be analyzed to provide information about a specific detail. A patient's medical history could be analyzed to provide the best treatment.

What's next for App Health DB

In the future, we hope it is used with machine-learning algorithms to better predict the type of treatment patients should recieve based on analysis of their history. This would ultimately be another way in which further advancements in precision medicine can be made.

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