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Hi HN, submitting from a burner since I'm an applicant this current medical residency admissions cycle. I thought it was interesting to show the real world impl
by medicalthrow 1y ago
Hi HN, submitting from a burner since I'm an applicant this current medical residency admissions cycle. I thought it was interesting to show the real world implications of using LLMs to extract information from PDFs. For context, thalamus is a company that handles the "backend" for residency programs and all the applications they receive (including handling who to invite for interviews, etc). One of the more important factors in deciding applicant competitiveness is their medical school performance (their grades), but that information is buried in PDFs sent by schools (often not standardized). So this year, they decided to pilot a tool that would extract that info (using "GPT-5o-mini": https://www.thalamusgme.com/blogs/methodology-for-creation-and-processing-of-a-novel-transcript-normalization-tool-in-cortex-application-screening-and-review-platform https://www.thalamusgme.com/blogs/methodology-for-creation-a...). Some programs have noticed there is a discrepancy between extracted vs reported grades (often in the direction of hallucinating "fails") and brought it to the attention of thalamus. Unfortunately, it doesn't look like the main company is discontinuing usage of the tool.
Regardless, given that there have been a number of posts looking into usage of LLMs for numerical extraction, I thought this story useful would be a cautionary tale.
EDIT: I put "GPT-5o-mini" in quotes since that was in their methodology...yes, I know the model doesn't exist
- philipallstar 1y agoThank you for sharing this. It's astonishing that places like this will do almost anything rather than create a simple API to ingest data that could easily be pushed automatically.
- daemonologist 1y agoThe trouble is getting people to use your API - in this case med schools, but it can be much, much worse (more and smaller organizations sending you data, and in some industries you have a legal obligation to accept it in any format they care to send).
- simonw 1y agoI imagine they would love to create a simple API for this, but the problem is convincing thousands of schools to use that API. If all you can get are PDFs, attempting to automatically extract information from those PDFs is a reasonably decision to make. The challenge is doing it well enough to avoid these kind of show-stopper problems.
- a-dub 1y agothey're essentially an ATS SAAS for medical school, if they have enough schools or enough prestigious schools, they can ask for whatever they want and the applicant schools would oblige. cheeky way to make it happen overnight: give a slight advantage to transcripts that are submitted digitally- the conversion would be complete within months.
- avarun 1y agoIf you want to get sued, sure.
- deleted 1y ago[deleted]
- aprilthird2021 1y ago> this year, they decided to pilot a tool that would extract that info (using "GPT-5o-mini": https://www.thalamusgme.com/blogs/methodology-for-creation-a https://www.thalamusgme.com/blogs/methodology-for-creation-a...). Mind-boggling idea to do this because OCR and pulling info out of PDFs has been done better and for longer by so many more mature methods than having an LLM do it
- b112 1y agoWelcome to the world of greybeards, baffled by everyone using AWS at 100s to 100000s of times the cost of your own servers.
- lazystar 1y agospectre/meltdown, finding out your 6 month order of ssd's was stolen after opening empty boxes in the datacenter, and having to write RCA's for customers after your racks go over the PSU's limit are things ya'll greybeards seem to gloss over in your calculations, heh
- mattnewton 1y agoNit, I’d say as someone who spend a fair amount of time doing it in the life insurance space, actually parsing arbitrary pdfs is very much not a solved problem without LLMs. Parsing a particular pdf is, at least until they change their table format or w/e. I don’t think this idea is totally cursed, I think the implementation is. Instead of using it to shortcut filling in grades that the applicant could spot check, like a resume scraper, they are just taking the first pass from the LLM as gospel.
- simonw 1y agoRight - the problem with PDF extraction is always the enormous variety of shapes that data might take in those PDFs. If all the PDFs are the same format you can use plenty of existing techniques. If you have no control at all over that format you're in for a much harder time, and vLLMs look perilously close to being a great solution. Just not the GPT-5 series! My experiments so far put Gemini 2.5 at the top of the pack, to the point where I'd almost trust it for some tasks - but definitely not for something as critical as extracting medical grades that influence people's ongoing careers!
- alexpotato 1y agoIt's amazing how much of "inter organization information flow" still happens over PDFs and/or just FTP'ing files around. A couple jobs ago at a hedged fund, I owned the system that would take financial data from counterparties, process it and send it to internal teams for reconciliation etc. The spectrum went from "receive updates via SWIFT (as in financial) protocol" to "small oil trading shop sending us PDFs that are different every month". As you can imagine, the time and effort to process those PDFs occasionally exceeded the revenue from the entire transaction with that counterparty. As others have pointed out: yes, the overall thrust of the industry is to get to something standardized but 100% adoption will probably never happen. I write more about the FTP side of things in the Twitter thread below: https://x.com/alexpotato/status/1809579426687983657 https://x.com/alexpotato/status/1809579426687983657
- jaggederest 1y ago> the time and effort to process those PDFs occasionally exceeded the revenue from the entire transaction with that counterparty. I'm interested in what the conditions were that didn't let you reject those kind of transactions, or blacklist them for the future. We hear about companies firing/banning unprofitable customers sometimes, surprised it doesn't happen more often honestly.
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- apt-apt-apt-apt 1y agoYou are so brave. I get like 8 spammers calling me daily about loans like I owe them money, and that's without blasting my phone number out to the internet.
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- mandeepj 1y agoI have it, but you still have junk in missed calls and voicemails.
- motbus3 1y agoI started receiving spam calls lately again but I was just denying the calls. It was with a predictable frequency few times a week. weeks ago I decided to use screening call, and maybe it was a coincidence, after the first usage I've not no more calls from them
- lozenge 1y agoWhy don't they just email a form after/when you apply and you fill in all the grades in a structured data way? How many grades are we talking about here. Then the PDF would just be the proof that your grades were real.
- simonw 1y agoBecause you'd have to get thousands of schools to agree to using the same format.
- lozenge 1y agoDoes the student not have access to the grades? As they are applying to medical school, a few hours of drudgery form filling will still be the easiest part of the process.
- medicalthrow 1y agoIt's a bit complicated. Each school has their own grading system (some pass fail, others four tiered, others full letter grades). Additionally, there are reported distributions for each grade. Lastly, there's sometimes a summary statement at the end that usually says "X student was 'superlative'" and then a table at the end that says 'superlative' means top X% of class. On top of that, students may not get their full dean's letter that says all of this stuff. Basically, self reporting is very difficult to do given the amount of variability in grade reporting.
- zeven7 1y agoMaybe have the students verify their own grades extracted by the LLM?
- doctorpangloss 1y agoHow should medical residency work? Like how should admissions work, is the match doing what you would want it to do, is there a radical alternative, etc? You have our attention! Don’t tell me the grades should be gathered accurately. Obviously. Tell me something bigger.