Published On May 17, 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:
0:00 - 0:45 - Introduction: AI for Reading and Processing Medical Notes
0:45 - 2:00 - Understanding the Use Case: Scanning Patient Notes with AI
2:00 - 3:30 - From Napkin to EMR: AI Note Recreation
3:30 - 4:30 - Analyzing the Process: How AI Understands Handwritten Notes
4:30 - 5:30 - Integration into EMR: Enhancing Patient Records with AI
5:30 - 6:30 - GPT Vision: A New Tool for Clinical Note Processing
6:30 - 7:20 - Concluding Thoughts: The Future of AI in Clinical Documentation
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