How to use AI to read and process notes

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  • เผยแพร่เมื่อ 12 มิ.ย. 2024
  • When an emergency department physician treats a patient, they’re writing notes on a napkin at times, not the EMR. So how can AI help them get those notes into patient records faster?
    This is a really interesting use case for AI. In this case, it’s a mix of two different AI models: A vision model to convert the image to text and an LLM to write a structured note from the text.
    While this use case shows the two models acting independently, the merging of two models is an exciting new capability OpenAI’s GPT-4o “omnimodel” just announced this week!
    So how would this work inside an EMR? And is the output generated by two different AI models even accurate?
    You’ll have to watch below in today’s edition of #CodetoCare, my video series on AI & ML, to find out!
    If you have any specific questions, drop them in the comments. I’m enjoying your input and I might even make a video responding to them.
    Check out my LinkedIn: / donwoodlock
    Timecodes:
    00:00 - Intro
    00:19 - AI Note reading use case explanation
    03:03 - Digesting physician notes into a clinical system
    05:43 - Explanation of first GenAI model: GPT Vision
    06:02 - Interim outcome of napkin into text
    06:29 - Explanation of the second GenAI model: Regular LLM
    06:44 - Wrap up
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ความคิดเห็น • 3

  • @MalikHamid-ye8zb
    @MalikHamid-ye8zb 18 วันที่ผ่านมา

    Thanks DON! for this outstanding use case of the GENAI. Kindly make more videos on Gen AI applications in different domains as well. Make playlist about use cases of Neural Networks(DL), ML, CNN, RAGS, Transformers also. You way of teaching enables me to think in a critical way! Thanks for making more videos relating to use cases.

  • @manservice3211
    @manservice3211 19 วันที่ผ่านมา

    Hello Sir! Could you make videos on: what’s a transformer and what’s Langchain? Also videos on how to check the accuracy of gen AI use cases like summarizing, extracting features, etc would be very helpful. Thank you very much for your time.

  • @yogeshsuryamurthy5939
    @yogeshsuryamurthy5939 26 วันที่ผ่านมา

    Thanks Don, it's very useful and an out-of-the-box use case. What do you think about extending this to ED triage categorization and assisting providers by presenting a care plan (or protocol) based on the patient's medical history and current diagnosis?