OncoSupport

Supporting Cancer Patients to Wellness Through AI

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Inspiration

"OncoSupport," short for "Oncology Support," was inspired by one of our team members' personal experience with the treatment of Stage 4 Burkitt's leukemia. Throughout the course of her treatment, she frequently dealt with complex medications, the hospital's administrative demands, and the stress of the treatment process. What she had hoped for was a system that could help her organize and comprehensively understand the treatment journey.

What it does

Our product serves as a streamlined software that provides cancer patients with a visually appealing and easy-to-understand overview of their treatment and next steps. The patients' medical team will upload and maintain their medical records. Based on the data, OncoSupport AI will curate appointments for the patients schedule additionally will provide recommendations on task/events to due within thier free time as often, cancer patients struggle with activity to do outside of appointments. Through OncoChat, patients will be able to get answer questions if their doctor is unavailable. Furthermore, through our "Close Connect" feature, patients can grant friends and family access to view their treatment history and receive live updates.

How we built it

The UI was created within Figma and artwork was created by a teammate using Procreat. We built a web application consisting of four major components: the frontend, which displays the elements to the user, the backend, which processes data and sends it to the frontend, the database, which stores the data for future use, and artificial intelligence APIs to take advantage of AI content.

The frontend consists of Next.js, where developers can choose server-side vs. client-side rendering per page and easy routing, making it a good option for a frontend framework. In addition, we used Tailwind CSS, a utility-first library allowing for the inclusion of CSS classes inside HTML.

The database is SQLite, a relational database that stores various info from patients including patient information, potential health concerns or upcoming events.

We also incorporated artificial intelligence APIs to use AI-generated content in various aspects of our site. This includes AI recommendations on simple wellness exercises or physical activities and a medically-focused chatbot.

Lastly, to connect the database, AI APIs and frontend, we created a simple API from Python Flask to handle http requests from the frontend and provide an interface between the data and client.

Challenges we ran into

We ran into issues regarding the scale of our project. Our initial goal was too ambitious and we were unable to implement all of the features we had planned within the timeframe. Additionally, we ran into issues with how to effectively present the information to the user in an easy and accessible manner.

Accomplishments that we're proud of

We are pleased with our UI design. Our webpage is well-formatted and intuitively designed for an optimal user experience. We are proud of creating an aesthetically-pleasing and accessible medical system. We created a multi-page web application and implemented a navigation bar that divides the application’s functionality into different pages.

We are proud of leveraging new APIs. We utilized three different 3rd party APIs to provide a richer user experience with more information and functionality.

What we learned

We gained experience in developing a web application in a team-based environment. We experimented with new frameworks and ideas outside of our comfort zone.

What's next for OncoSupport

Some ideas for future extensions to our web application include user authentication and secure sign in, advanced AI Chatbox capabilities, facilitate connections between connections between patients and family/friends to view information/treatment (CloseConnect), and implement a medical interface

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