InforMED

An AI assistant condensing healthcare information for the less healthcare literate, increasing the rate of accurate diagnoses. Translatable term sets are provided as an alternative learning method.

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Inspiration

We originally formed this team because we both were interested in biases within the healthcare system! As we did research, however, we discovered that there isn't really a set solution to solve all of these issues within the healthcare system -- especially racial, gender, and location bias.

While reading an article about implicit bias, however, we discovered that bias can arise from lack of awareness within healthcare providers, and decided that it'd be a much simpler problem to address in a short timeframe.

Given that AI is a up and coming technology that can be used for the greater, we looked to models such as Chat-GPT and looked at other ways that AI is utilized in the real world.

The concept of the term sets came from looking from the perspectives of students who were looking to go into the healthcare field -- it's best to learn early!

What it does

Given that AI is a up and coming technology that can be used for the greater, we looked to models such as Chat-GPT and decided to adapt it after a healthcare-provider's role to enable the patient to provide their actual healthcare provider with the proper information they would need, expediting the diagnosis so that the patient receives the treatment and care they need as soon as possible.

Term sets are intended to help students and aspiring healthcare workers memorize terms to be able to assist those around them! For this to be enacted in a website, its functions would be similar to that of Quizlet.

But the format is much nicer and comes with pre-made diagrams! Example cards are easy on the eyes for those with disabilities, and summarizes the location, the definition, and common issues in bite-sized points to digest! Sources are also provided for the information and the diagram for those who want to explore the terms more in-depth.

There's also a translate feature for those with English as their secondary language to easily comprehend the information in their own language!

How we built it

Because this is an Ideathon entry, we didn't code it. However, we used SlidesGo, Canva, and Google Slides to create our pitch.

Challenges we ran into

Because we wanted to address something that wasn't that easily solvable, we were stuck at an impasse until we found a different way to address another bias within the healthcare system.

Accomplishments that we're proud of

We're proud that we were able to condense our pitch down to two minutes and nineteen seconds, and that we were able to come up with such a cohesive solution in a short timeframe.

What we learned

We learned that the impact of bias is deeply rooted in healthcare, and that computer science isn't always the right answer to address it.

What's next for InforMED

We were looking into implementing was recruiting research volunteers to create more sets and update the AI as needed. Additionally, we were looking into creating an Uber-style function to be able to provide those in rural areas with transportation to their healthcare facilities for free.

Built With

  • canva
  • google-slides
  • slidesgo
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