Elliot Schumacher

[Neal Khosla @nealkhosla]

1/ We are publishing the first proof that AI can reason as well as clinicians in live clinical environments. Our AI diagnosed ~2400 patients as accurately as board certified clinicians in a real environment and was 30 percentage points better than Google’s equivalent system.

[Elliot Schumacher @elliotschu]

5/ With RareScale, we saw a significant improvement, boosting Top-5 diagnostic accuracy up to 17% . Check out our full paper for details! https://t.co/FRrc00t5Vy

[Elliot Schumacher @elliotschu]

1/ Excited to announce our new preprint, Rare Disease Differential Diagnosis with Large Language Models at Scale: From Abdominal Actinomycosis to Wilson's Disease. We introduce a method that enhances rare disease diagnosis by combining LLMs with expert systems! @CuraiHQ 🧵

[Elliot Schumacher @elliotschu]

4/ RareScale uses an expert system and simulator to create structured cases, which are in turn fed into LLMs to create free-form dialogues. These dialogues allow us to train a rare disease candidate generator which can be used in combination with a black-box LLM.

[Elliot Schumacher @elliotschu]

3/ If you're in Vancouver this weekend, stop by to talk to me about our work or Curai!
- Saturday, 1pm at GenAI for Health
- Sunday, 4:45pm  at Machine Learning for Health

[Elliot Schumacher @elliotschu]

1/ 🧵 Excited to share that we are presenting our paper, "MED-OMIT: Evaluation Metric for Omissions in Medical Summarization," at #GenAIforHealth and #ML4H2024! 🎉.  Link :  https://t.co/KrD1Gx30F3

[Elliot Schumacher @elliotschu]

2/ By discretizing facts from source documents and assessing their significance to a downstream task (eg. diagnosis), MED-OMIT evaluates whether LLM-generated summaries retain all clinically important information for that task 🔎🩺

[Elliot Schumacher @elliotschu]

Great work Albert! Check out the paper at https://t.co/UvloKkYs2e .

[albert yu sun @Albertyusun]

Had a wonderful time presenting my paper from my internship last year with @CuraiHQ at #NAACL2024!

Grateful for the opportunity to talk to the awesome and thoughtful people in the NLP community.

@elliotschu @anithakan @nairvarun18

[Elliot Schumacher @elliotschu]

Thrilled that @Albertyusun's work was accepted at #NAACL main conference! 🎉 Check out the paper https://t.co/AypYJ0aq3I and see the thread for details.

[albert yu sun @Albertyusun]

Excited to announce that my internship work with my awesome collaborators at @CuraiHQ from last year has been accepted to the main conference @naaclmeeting 2024😃

Check out our work building practical guardrail models for LLMs using a diverse synthetic data generation approach!

[Anitha Kannan @anithakan]

@CuraiHQ We are hiring researchers & engineers to work on highly impactful problems at the intersection of AI and healthcare to bring affordable care to everyone. https://t.co/EFu4bU2rYC
https://t.co/QAKzlzOgIx
https://t.co/qoFrKDJALc

[albert yu sun @Albertyusun]

1/ New preprint!🔔

Excited to share my internship work at @CuraiHQ.

Using model distillation techniques, we’ve developed an approach to create light-weight guardrail models that monitor the output of generative language models like GPT-4!

w/@nairvarun18 @elliotschu @anithakan

[Varun Nair @nairvarun18]

Latest from @curaiHQ: DERA - Dialog-Enabled Resolving Agents!

We (@elliotschu, @gtsomd, @anithakan) use the conversational ability of GPT-4 to create an interpretable forum for agents to communicate and iteratively improve output. Thread 👇
https://t.co/ocqPScTxBB

[Mitchell Gordon @MitchellAGordon]

New blog post! This time I'm looking at recent advances in memory-efficient training and where that might lead.

https://t.co/gtSAQ3JcIF