oracle
i started off with oracle session as i hadn’t really attended industry panels. i enjoyed some of the acronyms, like “stormed and normed.” also, the idea that oracle as a big company was late to the cloud / others had years ahead, so to catch up they hire the eng that build other clouds and ask for better faster cheaper. (?!)
from words to wonder
i dropped by there – so it appears that for some tasks fine-tuned bert is still performing better even than latest llm on token-level NER vs. document level NER (not entirely sure what this means). this makes sense since llm is trained for causal prediction (next token) vs . embeddings may have more sense of individual words (bidirectional) and may be better suited for such classifciation tasks. i found it interesting that they point out limitations that there are other ways to instruct llms – for my own research i found it difficult to figure out how many prompts i should use to feel confident in my results. i guess … just one lol
food entities
this paper looked more at zero shot and one shot for identifying food entities from patient generated data. chatgpt performed a lot better than rule-based systems trained on fairly clean data, since it could handle stuff like “bbq” for barbecue and “happy meal” for mcdonalds. the research was excited that we can now use more varied data without tailoring algorithms across datasets.
bioner
i finally got an order of magnitude sense, the presenter said that fine tuning the llm directly took around 30 mins on 4x A100 18 GB gpus. but other methods include llora and parameter efficient fine tuning (peft). interesting point to just say that there was not statistically significance for some of comparisions
nih common data element normalization
again emphasis that ensemble methods perform better. i guess this is true for humans too!
nabla
i also went to Q&A part of nabla, it was cool to sit in a room of practicing clinicians vs. rooms of fellow researchers that are slightly adjacent to my work. (i also miss the extremely technical nerds sometimes). i created a mastodon account (to use every half year or so between conferences? next time i’ll add it to my badge):
TIL: paperwork burden big driver of provider burnout (!), and “Ambient AI” shortens from 90 mins to 30 mins = can go home and spend time with family in evening, can see more patients #amia2024 nrobot@mastodon.social
i had no idea that the paperwork was so severe that it actually drives burnout. but it makes sense if it’s taking an extra 1.5 hrs of your life after work to catch up on all the paperwork !!
also this interesting quote “gen AI scribing [note to summary] is like ice cream — there’s some people who like it, but not many!”
WIG NLP
then i learned a bit about working groups, still not entirely sure what they are, but i have to be an AMIA member to access anyway (vs just attending the conference). they were trying to set up a mentor / mentee network but kind of struggling. in general i’ve noticed there’s less willingness to randomly connect and mentor than i expect. especially i heard fabled west coast startups willingness to help each other out. maybe it’s that there are many high level industry execs here.
yale – emulated clinical trial
trying to find cohort retrospectively — realized the biggest issue (spent years) is the messiness of the data. normal clinical trial is 100% accurate. if you have 6 parameters that have to be pulled out with nlp, and the current state of art is 80-90% accuracy, that comes down to 30-50% accuracy which is unacceptable for running an emulated clinical trial.
generally
i’ve heard a lot about how finding patients (and others aspects) of clinical trials are slowing down research in a major way. so there’s a ton of research into how to address this.
posters
then i caught up with my coworkers posters! since i have most reference on this i’ll post more later. basically presenting on the system side of a pilot to rank patients for screening, anecdotal catching patient with cancer that wouldn’t have been caught by old system. rolling out pilot to 28 hospitals soon. the clinicians present on the outcomes side of impact on patients, vs the informatics group presenting on rapid system roll-out
here i’ve started talking to random posters and connecting with people. i think i was just talking to people that were too busy / high level before. humbling for sure, and also confusing coming from socializing in startup circles i guess as i never integrated well into higher education :'(
TIL: paperwork burden big driver of provider burnout (!), and “Ambient AI” shortens from 90 mins to 30 mins = can go home and spend time with family in evening, can see more patients
generally
the nicest seminar was still the keynote on sunday, not sure if that’s because i’m flitting in and out of sessions instead of sticking in one session and talking to people
i skipped out on an entire half session, just went to sit and read a book. the sensory room is just a small conference room set on a different floor, but it was chairs at tables, no comfy couches, so i went to the lobby and sat in a comfy couch instead and put in headphones. actually that place was incredibly loud but it worked haha
dei event
i would not have gone on my own, at this conference i feel like not-minority lmao. but i went with my coworkers and the industry sponsor provided good food. at first it was just a few people and we stood by ourselves, but the chair / co-chair came to talk to us, and by the time that finished the room was incredibly full. i was really impressed by one of them who could tell that ray and rui are pronounced differently (rui has the tongue further back), legit thought he did linguistics. he connected it to christian beliefs which i found interesting, that the lord knew our true name before we were born, so really pronouncing names is important to him. i didn’t connect with anyone new (too burnt out) but i reconnected with folks from WINE.
career talk
i talked to one person about my life goals, and that was a good talk. i should likely not treat my supervisor as anything adversarial. i admit that it threw me off for him to say that i would be working under my coworker so that was the more important opinion for performance evals. and it has made me mrrr to hear that i should be doing the work of the position i want when i am being paid half the cost of that position to do that much work. but i do not think my supervisor meant to imply i would be working under my coworker no matter what.
VA event
there was also a VA event that we dropped by, but everyone there was super tired so we talked to one group of people and left. i again felt some regional politics at play slightly.
personal
okay, i feel like i’m totally at failing at connecting with people, but have to remind myself i’m like … 2 days into getting to know people here. and two months into having some new blurb to write about myself.
it’s been incredibly relaxing even if possibly fool hardy to not go around the exhibition hall trying to connect with companies.
also there is so much i need to learn, that i can feel free to list now that i have a job and a foot in the door (and emotional reserves). likert, rouge, llora, spearman, these are all terms i need to learn. maybe i’ll install chat on my phone just so i can learn those in the moment as i’m motivated and there’s context for how it’s used …
prior self
i can see how i must have come across to people before i got a job now. just kind of emotionally disconnected from everyone else, not wanting people’s pity and knowing they can’t help right away, and feeling so hopelessly caught up in my own life issues. i keep trying to remind myself. one day when i struggle to go to the bathroom on my own i’ll look back on this time in my life and be like “wow that was such a good time.”
or maybe i’ll get cancer earlier and just wish i had such normal problems where i thought i would live to old age. i’ll miss the time when i could still just call my parents and they didn’t have major health problems and i still had hope for them to live to 120. who knows, who knows.
general state of the world
i feel surprisingly detached from all my anger and fear about the elections in the united states. it barely takes up 1% of my mental headspace. it’s like 50% industry career new job, 30% technical skills worry, 15% relationships, 4% excitement about extremely random stuff on my backburner, 1% state of domestic and international world affairs / bitterness (how could we have someone who molests women as our president? and millions of people turned out to vote for him? i feel such shame and horror and despair and hopelessness that kamala harris is not our next president. all my degrees and accomplishments feel utterly useless. i feel so angry, so angry at anyone in my life that doesn’t hate trump. but remember — the world is not ending today or tomorrow, my friends can ally with me on other things, and my life will be okay).
high level planner
i’ve been trying to move in the opposite direction of my natural instincts. if i’m drawn to the climate and diversity and equity talks, i’ve been forcing myself to go in more purely technical directions. i would like to find my own pure happiness in technical implementation for the next few years independent of the impact. of course, from my perspective any work i do on AI is work I’m not doing on equity in AI and contributing to climate change in data centers. i’m not living up to my principles and the emotional energy i directed at it. but reminding myself that the alternate pathway is: get rich, make changes, donate to causes and empower others to work on these topics. i feel after my thesis on illicit massage industry and the energy i put into supporting my ex partner, it’s time to focus on just me. and nothing has to be permanent. it’s like i constantly have a higher-level planner — what should i be spending my time thinking about? usually the answer is, not what i’m thinking about right now. and it’s important but hopefully i can start tuning it down some day soon. i want to be thinking about interesting technical papers, where the field is going, cool packages i learned about recently, learning about monads and the latest bug in some code i wrote. hopefully next week i can finally start doing that.