AI + expertise paradox. More technical and specialized medical tasks -> easier for AI to substitute & outperform _average_ human experts. Case in point is echocardiogram interpretation. Yet it is those tasks that are better paid/reimbursed vs general primary care. HT @venkmurthy
Epic Systems makes the dominant electronic health record (EHR) system in America; if you're a doctor, chances are you're *required* to use it. For each hour a doctor spends with a patient, they spend *two* hours on clinically useless bureaucratic data-entry on an Epic EHR.
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Interested in using LLMs to automate writing clinical notes?
Remember stories like this, which happen all the time.
Writing = thinking. LLMs can and do help us think, but not if they are implemented thoughtlessly.
We write so much useless research that no one reads that we now have invented a new type of useless research that no one reads -- the "scoping review".
As clinicians spend more time reading/writing notes, Sharon Jiang, Barbara Lam, @MonicaNAgrawal, @shannonzshen, Nicholas Kurtzman, Steven Horng, @karger, & @david_sontag propose an ML approach that predicts relevant clinical notes in @JAMIA_Journal https://t.co/OnXCwfIzUm
How to be as "smart" as Auto-Regressive LLMs:
- memorize lots of problem statements together with recipes on how to solve them.
- to solve a new problem, retrieve the recipe whose problem statement superficially matches the new problem.
- apply the recipe blindly and declare victory.
- do not use basic logic.
- do not use common sense to check your solution.
- do not use a mental model of the situation as a sanity check.
- do not simulate the scenario in your mind using your world model.
- when someone tells you your solution is wrong, reply "I'm sorry, you are right" and apply another irrelevant recipe.
Knowledge accumulation is not a substitute for actual understanding.
Very proud of the @PathwayMedical team for this one.
Explored every drug API to build this, but nothing was quite labeled and granular enough for our needs.
Built a drug database from scratch - a monumental task, unlike any other challenge we've tackled.
More to come!
🚀 DeepSeekMath: Approaching Mathematical Reasoning Capability of GPT-4 with a 7B Model.
Highlights:
- Continue pre-training DeepSeek-Coder-Base-v1.5 7B with 120B math tokens from Common Crawl.
- Introduce GRPO, a variant of PPO, that enhances mathematical reasoning and reduces training resources.
More Details:https://t.co/lw5u1BWK3U
Model Download:https://t.co/d06dFvQp8r
GitHub Repo:https://t.co/0FQdIuPLNW
#DeepSeek #DeepSeekMath
@jonathanhershon Agreed with all the points made! I would also add that it is essential that whatever the solution is, it needs to integrate seamlessly into physicians workflow.
@itsdrhartmann @naval We do this at @PathwayMedical
Our AI generates answers based on high-yield, evidence-based literature and our structured medical knowledge graph.
Physicians love it so far.
@naval AI will not replace docs, but it will augment them. We're already doing this at @PathwayMedical - our AI searches across all high-yield medical literature and gives fast, concise, and reference-backed answers to clinical questions in seconds.
I left Gaza yesturday.
My heart and my soul are still there with my patients. I remember their names and their wounds. I will fight until they receive the treatment they need and the justice they deserve.
My heart is broken in ways I never knew was possible.
Triste constat qui rappelle l'aspect clé de l'IA en santé : définir des problèmes réels pour lesquels des solutions sont implémentables. #polqc
https://t.co/SeOQC5xe4L