Colour coded original transcription text to increase use in supervision and teaching of clinicans
Nicola Holmes
Hi Guys, firstly thank you so much for changing my life and preventing burn out and getting me back into loving why I do medicine! As a teacher and supervisor it would be useful to have the original transcript text colour coded so you can easily identify when the patient is speaking (say black) and when the clinican is speaking (blue) and maybe a third colour for other random speakers eg kids. This would be useful for feedback when reveiwing consultations, instantly you see who is doing most of the talking and can finely look into details eg see how you interrupted them here....etc. Thanks again you heros.
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Andrea
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easier to read transcript
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Yellow Bird
Can transcript be separated into paragraphs when pauses occur OR beter still as per Otter - separated into doctor .... and patient .......
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Andrea
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Speakers in transcriptions
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Ryne Zuzinec
I'd like to see speakers listed in the transcription.
Canny AI
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Re-format the transcript so it can be read like a script-write to improve its readability.
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Joseph Ormerod
There are various scenarios where going back to the whole transcript is useful. At the moment the format of the transcript is very basic and hard to read. I propose some templating is needed to make this more legible.
e.g.
Clinician speaks: "transcript"
Patient speaks: "Transcript"
Clinician speaks: "transcript"
Patient speaks: "Transcript"
Time stamps would be nice too.
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Andrea
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The transcripts do not recognise different speakers
Adhiraj Joglekar
If as a clinician I asked - are you still continuing to have pain ... the AI generated summary mistook this as patient saying they are continuing to have pain.
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Sarah Sultan
I find this happens a lot—plus Heidi confuses speakers, even when they have distinct voices. Once, I described a scintillating scotoma and Heidi mistakenly added “migraine with classical aura” to the pt's note—with an updated history and detailed treatment recommendations! Even when I clarify it's the physician speaking, Heidi will still misattribute info. Sometimes, I avoid casual conversation just to prevent errors. Yet Heidi will also dismiss crucial, extended interactions as small talk. AI is impressive but a work in progress.
Canny AI
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Speaker detection in transcript tab
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Andrea
Heidi to identify different speakers in a session, eg Speaker 1, Speaker 2.
Canny AI
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Voice recognition
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Ira Bilofsky
One thing that helps is voice recognition for the user. This way, Heidi knows how to separate two male voices, which is then identified as the patient even though the discussion is back-and-forth between two males.
Canny AI
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Multiple people in the room
J M
I’m noticing that heidi is not picking up on multiple voices from family members and thus the note does not reflect who did most of the speaking, etc
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Thirumaran Rajathurai
I agree with this. It would be great if Heidi could distinguish between different speakers, eg. patient vs relative
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Thirumaran Rajathurai
I agree with this. It would be great if Heidi could distinguish between different speakers, eg. patient vs relative
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