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Andrew Sellergren Profile
Andrew Sellergren

@asellerg

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194
Following
739
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Statuses
134

Triathlete | Coach | Software Engineer @Google

Joined July 2009
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@asellerg
Andrew Sellergren
3 years
Find out more about our tool on our GitHub page: https://t.co/InDMvepCRD
@sundarpichai
Sundar Pichai
3 years
A new #GoogleAI tool reduces the size of datasets needed for radiology models used to predict abnormalities in chest x-rays, making it easier for researchers to build custom models that can help in disease detection. https://t.co/IFSz5kMgE3
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@emollick
Ethan Mollick
4 months
MedGemma is a really interesting model - very small, multimodal, open, and does quite well in out-of-distribution medical tasks compared to much larger models. Would love to see more work thinking about how to improve & deploy this sort of LLM to support medical professionals
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@_philschmid
Philipp Schmid
4 months
The @GoogleDeepMind Gemma family of open models continues to grow! Today we launched T5Gemma a new take for encoder-decoder models and a new multimodal version of MedGemma with a specialized SigLip variant for healthcare. 🚀 T5Gemma: - Adapts Gemma 2 into flexible
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@JeffDean
Jeff Dean
4 months
Check out our state-of-the-art open weights MedGemma multimodal model for making sense of longitudinal EHR data as well as medical text and medical imaging data in various modalities (radiology, dermatology, pathology, ophthalmology, etc.) See the blog post linked below! ⬇️
@GoogleResearch
Google Research
4 months
Introducing new models for research & development of health applications: MedGemma 27B Multimodal, for complex multimodal & longitudinal EHR interpretation, and MedSigLIP, a lightweight image & text encoder for classification, search, & related tasks. → https://t.co/I318jVmsYD
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@osanseviero
Omar Sanseviero
4 months
🏥Introducing MedGemma, part 2, including: 🔥A 27B multimodal MedGemma 👀MedSigLIP, a lightweight image/text encoder for medical image retrieval/classification 📜A technical report with details Blog: https://t.co/UGgTZOGrOo Paper: https://t.co/LGhr9ai1Hl
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@SRSchmidgall
Samuel Schmidgall
4 months
The MedGemma technical report is out 👇 https://t.co/6ZxcKqFgMK
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@GoogleResearch
Google Research
4 months
Introducing new models for research & development of health applications: MedGemma 27B Multimodal, for complex multimodal & longitudinal EHR interpretation, and MedSigLIP, a lightweight image & text encoder for classification, search, & related tasks. → https://t.co/I318jVmsYD
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@GoogleForHealth
Google for Health
4 months
The MedGemma collection consists of our most capable open models for health AI development. Today we're announcing two new additions to the collection: MedGemma 27B multimodal and MedSigLIP.
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@mervenoyann
merve
5 months
Google released MedGemma on I/O'25 👏 > 4B and 27B instruction fine-tuned vision LMs and a 4B pre-trained vision LM for medicine > available with transformers from the get-go 🤗 they also released a cool demo for scan reading ⤵️
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@GoogleForHealth
Google for Health
5 months
Exciting news from #GoogleIO! We’re introducing MedGemma, our most capable open model for multimodal medical text and image comprehension built on Gemma 3.
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@AziziShekoofeh
Shek Azizi
11 months
This week we announced ✨𝐇𝐞𝐚𝐥𝐭𝐡 𝐀𝐈 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 𝐅𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧𝐬 (𝐇𝐀𝐈-𝐃𝐄𝐅)✨ which is a collection of open weight models to accelerate the development of health AI for real clinical use-cases.
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@dgtbarrett
David Barrett
1 year
Excited to share our work on ‘Collaboration between clinicians and vision–language models in radiology report generation’, published today @NatureMedicine (1/N). https://t.co/KIxBvwGp38
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nature.com
Nature Medicine - By engaging a group of 27 certified radiologists in the United States and India, the accuracy and quality of radiology reports generated by a vision–language model is...
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@GoogleColab
Colaboratory
1 year
Our friends at Google Research used Colab to interface with their new models! Check out CT Foundation, a new medical foundation tool that helps you train models on CT scans in Colab. Read and sign up here for access:
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research.google
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@AziziShekoofeh
Shek Azizi
1 year
Built on our work from ✨Med-Gemini✨, we're thrilled to unveil ⚡️⚡️CT Foundation⚡️⚡️, a novel AI endpoint that simplifies CT scans analysis!
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@GoogleAI
Google AI
1 year
Announcing CT Foundation, a new medical imaging embedding tool that accepts a computed tomography (CT) volume as input and returns a small, information-rich numerical embedding that can be used to rapidly train models. Learn more and try it out yourself → https://t.co/AFXAj5edTE
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@asellerg
Andrew Sellergren
1 year
@cs50 Gambol is very much in beta (for example, it only works for 2-player situations at the moemnt), but I wanted to get something out there to see if it would be useful and interesting to people. Feel free to reach out with comments and questions!
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@asellerg
Andrew Sellergren
1 year
I officially started Gambol over 4 years ago at the beginning of the pandemic and evolved it more recently with the latest advancements in GenAI. But really I started it 17 years ago as my final project in @CS50 which *may* have been a little ambitious for the time...
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@asellerg
Andrew Sellergren
1 year
If you don't have a specific hand in mind or you want to do some studying, just click the Random button to pick an interesting post-flop situation.
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@asellerg
Andrew Sellergren
1 year
Once Gambol has given you the GTO strategy, it will explain it using poker theory. Then you can ask follow-up questions, for example asking it to explain the poker terms it just used.
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@asellerg
Andrew Sellergren
1 year
On the backend, Gambol has been trained just like Pluribus, the first superhuman multiplayer Texas Hold'em AI, using counterfactual regret minimization (CFR) to find the game theory optimal (GTO) strategy for a given situation.
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@asellerg
Andrew Sellergren
1 year
Just in time for the World Series of Poker, I taught Gemini to play Texas Hold'em! Meet Gambol ( https://t.co/mYnHdrsCce), an AI coach for 6-max Texas Hold'em. Describe the hand including your hole cards, the action, and the board and Gambol will tell you the optimal strategy...
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