CancerCost

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Inspiration

In this day and age, AI has seen greater and greater usage, especially in the online world. We were inspired by websites that use AI to improve user experience and incredibly impressed by its ability to find and sort information effortlessly.

What it does

Our innovative website allows for users to calculate the approximate range they could expect their cancer treatments to cost. It asks the user some key questions and uses the user's input to match with previously collected data from other sources to determine the expected costs. This allows for the users to plan around the potential financial burdens and seek support.

How we built it

Our project is a website built from HTML5, JavaScript, and CSS. We each tackled a section, with one of us handling the HTML, and two of us working on the JavaScript and CSS. The website itself is powered by the Google Gemini API, which sorts the data gathered from our sources and presents it in a user-friendly manner.

Challenges we ran into

One of our greatest challenges was finding reputable sources with large pools of data for Google Gemini to use. Eventually, we were able to use AI to give us lists of sources with data, and from there we could manually sort through the ones that were reputable and send it to Gemini to use.

Accomplishments that we're proud of

We are very proud of our Chatbot that we were able to integrate into our website. The Chatbot is able to answer cancer related questions that the website may otherwise not be able to provide, as well as potential steps to take after learning of the costs.

What we learned

We gained a deeper understanding of the workings of AI. Our coordination also made great improvements, as we tried to communicate our changes within the same files.

What's next for CancerCost

Right now, we are providing the AI with the sources and data to use. However, the number of sources we have provided is limited. in the future we would like the AI to be able to find its own reputable sources and data, so that there is a larger sample size and predictions become more accurate. We ultimately hope to be able to provide higher quality information that is more recent and reliable, as to improve user experience.