Absolutely and it has done so for over a decade. Not LLMs of course, those are not suitable for the job but there are lots of specialized AI models for medical applications.
My day job is software development for ophthalmology (eye medicine) and people are developing models that can, for example, detect cataracts in an OCT scan long before they become a problem. Grading those by hand is usually pretty hard.
So… The medical professional is taking voice notes and then they get transcribed (ok, this is fine) - and then summarized automatically? I don’t think the summary is a good idea - it’s not a car factory, the MD should get to know my medical history, not just a summary of one.
You can’t make an LLM only reference the data it’s summarising. Everything an LLM outputs is a collage of text and patterns from its original training data, and it’s choosing whatever piece of that data seems most likely given the existing text in its context window. If there’s not a huge corpus of training data, it won’t have a model of English and won’t know how to summarise text, and even restricting the training data to medical notes will stop mean it’s potentially going to hallucinate something from someone else’s medical notes that’s commonly associated with things in the current patient’s notes, or it’s going to potentially leave out something from the current patient’s notes that’s very rare or totally absent from its training data.
If you end up integrating LLMs in a way where it could impact patient care that’s actually pretty dangerous considering their training data includes plenty of fictional and pseudo scientific sources. That said it might be okay for medical research applications where accuracy isn’t as critical.
Absolutely and it has done so for over a decade. Not LLMs of course, those are not suitable for the job but there are lots of specialized AI models for medical applications.
My day job is software development for ophthalmology (eye medicine) and people are developing models that can, for example, detect cataracts in an OCT scan long before they become a problem. Grading those by hand is usually pretty hard.
Can you tell me more about your job, as fellow computer guy I would really appreciate first hand experience.
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So… The medical professional is taking voice notes and then they get transcribed (ok, this is fine) - and then summarized automatically? I don’t think the summary is a good idea - it’s not a car factory, the MD should get to know my medical history, not just a summary of one.
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You can’t make an LLM only reference the data it’s summarising. Everything an LLM outputs is a collage of text and patterns from its original training data, and it’s choosing whatever piece of that data seems most likely given the existing text in its context window. If there’s not a huge corpus of training data, it won’t have a model of English and won’t know how to summarise text, and even restricting the training data to medical notes will stop mean it’s potentially going to hallucinate something from someone else’s medical notes that’s commonly associated with things in the current patient’s notes, or it’s going to potentially leave out something from the current patient’s notes that’s very rare or totally absent from its training data.
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If you end up integrating LLMs in a way where it could impact patient care that’s actually pretty dangerous considering their training data includes plenty of fictional and pseudo scientific sources. That said it might be okay for medical research applications where accuracy isn’t as critical.
deleted by creator