COLO COMPANION

Streamlit
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Created by team FutureTech Mavericks on November 10, 2023

Our work involves the development of a medical chatbot that specializes in colorectal cancer. This chatbot is designed to provide consultation and support to individuals dealing with colorectal cancer. The primary goals of the chatbot include raising awareness about it, offering instant support to patients, and reducing the risk of misinformation. It aims to harness the power of technology to make a positive impact on the lives of individuals affected. We are contributing to the broader efforts in healthcare to improve patient support, increase awareness, and enhance the overall experience of these patients. It's a commendable initiative that aligns with the evolving landscape of healthcare and technology integration.

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"Idea looks nice and good presentation, but ultimately the output of Vectara (text variable) seems dangling and not use in the output. "

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Ofer Mendelevitch

Head of DevRel

"- Good, mission-driven scenario that the application is looking to address. The presentation was good, but I would have liked to see a summary, and perhaps some next steps or thoughts on how you can make this available to people. - There is a good focus on the human element of the application. Very important in this domain. But it did not let me ask a follow up question to the bot. - Clean, well structured repo with a good readme. "

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Justin Hayes

Head of Field Engineering

"It looks like the summary from Vectara is then being fed into Anyscale llama2, instead of the search results. Maybe data wasn't loaded into Vectara? I could only find a single PDF in, which didn't have much information in it. As a result, this hallucinates quite a bit, citing sources that don't exist. I asked a few questions in the demo and the cited sources sent me to https://www.mayoclinic.org/diseases-conditions/colorectal-cancer/symptoms-causes/syc-20363775 and https://www.cancer.org/cancer/colon-rectal-cancer/causes-risk-factors.html, neither of which exists. I think the submission would be much more compelling if, instead of taking the Vectara summary, it took the list of results from Vectara and then sent them to Anyscale. This would allow for many of the benefits of retrieval augmented generation, including proper citation citing, which is critical for a use case like a medical chatbot"

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Shane Connelly

Head of Product