BerriMed

Inspiration

Having extensive personal experience searching for medical help, we've always been fascinated by the potential of technology to revolutionize healthcare. We realized that healthcare professionals often need to access the latest medical research to make informed decisions, but the sheer volume of information available can be overwhelming. We wanted to create a tool that could streamline this process and provide real-time access to medical knowledge. This idea inspired us to create "BerriMed," a real-time personal medical assistant powered by PubMed, for the hackathon.

How we built it

We started by researching available APIs and tools that could help access PubMed's vast database of medical research. We chose to use the PubMed API to query the database and retrieve relevant articles based on user input.

Challenges we ran into

One of the main challenges we faced was handling the vast amount of data returned by PubMed for certain queries. We had to find a way to filter and prioritize the most relevant articles while ensuring that the response time was acceptable for real-time use.

Another challenge was understanding and processing complex medical terminology. We had to ensure that BerriMed could interpret user queries accurately and provide information that was both accurate and understandable to users without medical backgrounds.

Accomplishments that we're proud of

Despite the challenges, we're proud of what we accomplished with BerriMed and are excited about its potential to improve access to medical knowledge for healthcare professionals and the general public alike.

What we learned

Throughout the development of BerriMed, We learned a great deal about how to work with Berri's out-of-the-box APIs, LLMs, and being creative with domain specific python libraries. We gained a deeper understanding of how to extract and process relevant information from medical research articles. Additionally, we learned about the importance of user experience and how to design an intuitive interface that allows users to interact with the medical assistant seamlessly.

Built With

• berri
• bio
• openai
• python
• replit