Dr. Noel Codella, Ph.D.

Principal Researcher @Microsoft. Ph.D. @WeillCornell. M.Eng. @Cornell. B.S. @Columbia. Machine Learning. Human Physiology. Opinions expressed are my own.

[Dr. Noel Codella, Ph.D. @NoelCodella]

Our Florence #computervision model was recently featured in an article in @TheEconomist about #ArtificialIntelligence and foundation models:

https://t.co/3vxAIYhncH

#MachineLearning #Microsoft @Azure

[Fernando Pérez-García @fepegar_]

We are excited to release the weights of @MSFTResearch's COLIPRI, our 3D vision–language encoder for chest CT scans, on @huggingface🤗

Model: https://t.co/qmhZU6zNc8
Demo: https://t.co/uDiz3NDKlq
Paper: https://t.co/hbFWFpaPXv

Why does COLIPRI matter?

🧵0/12 👇

[Alyssa Unell @AlyssaUnell]

1/🧵 Introducing CancerGUIDE: Cancer Guideline Understanding via Internal Disagreement Estimation. Can LLMs give guideline-concordant cancer treatment advice in data-sparse settings?

🏥Our new framework tests LLMs on guideline adherence in real cancer cases.

👇 #AIinHealthcare

[Matthew Lungren MD MPH @mattlungrenMD]

We have seen many ways that generative AI can transform healthcare but over-stretched health-IT teams can’t deploy new software systems to surface the latest advancements fast enough.

But... what if developers could meet clinicians where they already work today, building, deploying, and testing AI capabilities that address challenging complex clinical tasks in minutes, not months?

Thats why today we’re announcing the launch of Healthcare Agent Orchestrator bringing the latest cutting edge AI into the hands of healthcare users leveraging Azure AI Foundry and surfacing into M365 enterprise software that health systems globally already use and trust - check out this blog to learn more: https://t.co/cLRS9R016a

[Matthew Lungren MD MPH @mattlungrenMD]

Excited to share our open-source code for cancer survival prediction using radiology (MRI) and pathology (H&E) images - this walkthrough uses our lightweight domain specific multimodal medical imaging embedding models + adapters to produce hazard scores and survival probabilities. Trainable on CPU in minutes!

Details and code: https://t.co/jjdzp3gf2B
Blog post: https://t.co/7VUEikzLAA

[Cyril Zakka, MD @cyrilzakka]

Due in part to the large number of runaway takes in medical AI, I'm launching a regular thread to spotlight noteworthy and more leveled research papers in the space and/or related fields with promising applications in healthcare.
RTs appreciated. Let's begin!

[Dr. Noel Codella, Ph.D. @NoelCodella]

Paper: https://t.co/Ru1rZa5Bvh

[Dr. Noel Codella, Ph.D. @NoelCodella]

Our team within Microsoft Health and Life Sciences is happy to announce the release of MedImageInsight, an open-source medical imaging embedding model. (1/n)

[Dr. Noel Codella, Ph.D. @NoelCodella]

Blog: https://t.co/i0jGgXbBZr

[Dr. Noel Codella, Ph.D. @NoelCodella]

@zsoltkira @mlatgt @ICatGT Congratulations!!!

[Fernando Pérez-García @fepegar_]

🔥 Our new preprint on biomedical self-supervised learning with images only is out! 🔥

Rᴀᴅ-DINO: Exploring Scalable Medical Image Encoders Beyond Text Supervision
by @MSFTResearch

We show that:

0/3 🧵

[Dr. Noel Codella, Ph.D. @NoelCodella]

@RoxanaDaneshjou Congratulations!!