Guy Lutsker

33 posts

Guy Lutsker

Guy Lutsker

@GLutsker

PhD student at the Weizmann Institute of Science

Israel Katılım Haziran 2018
676 Takip Edilen93 Takipçiler
Guy Lutsker retweetledi
Eran Segal
Eran Segal@segal_eran·
Our two new arxiv papers achieve state-of-the-art (SOTA) performance on multiple long-term time-series forecasting tasks, using way fewer parameters than previous SOTA models. Our models are based on mixture of expert transformer architectures Papers: arxiv.org/abs/2601.21641 arxiv.org/abs/2601.21866 Great work by Evandro Ortigossa and @GLutsker
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David Sinclair
David Sinclair@davidasinclair·
The future is already here: An AI model built on continuous glucose monitoring (CGM) data predicts Type 2 diabetes and cardiovascular deaths better than the standard biomarker, HbA1c
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nature
nature@Nature·
Nature research paper: A foundation model for continuous glucose monitoring data go.nature.com/4602eqO
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NVIDIA Healthcare
NVIDIA Healthcare@NVIDIAHealth·
🚀 GluFormer, a transformer model trained on 10M+ glucose readings, predicts diabetes and cardiovascular risk up to 12 years ahead - outperforming HbA1c. Built by NVIDIA Israel, @WeizmannScience, @Pheno_AI, and clinical partners. 📄 nvda.ws/4rnWIa7
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Eran Segal
Eran Segal@segal_eran·
Sharing Gluformer, our latest paper @Nature: The first generative foundation model for blood glucose data, trained on data from 10,812 adults of the Human Phenotype Project Gluformer predicts risk of diabetes and cardiovascular outcomes better than the standard of care Full paper: rdcu.be/eY5fH Collaboration of @WeizmannScience @mbzuai @nvidia @Pheno_AI Work by @GLutsker Gal Sapir, @smadarshilo, Jordi Merino, @nastya_godneva, Jerry R. Greenfield, Dorit Samocha-Bonet, Raja Dhir, Francisco Gude, Shie Mannor, Eli Meirom, @ericxing, Gal Chechik, and @H_Rossman
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Eric Topol
Eric Topol@EricTopol·
Continuous glucose monitoring sensor data, with a foundation model, predicts risk of Type 2 diabetes and cardiovascular outcomes better than HbA1c New @Nature @segal_eran @WeizmannScience @GLutsker "66% of incident diabetes cases and 69% of cardiovascular deaths occurred in the top risk quartile, compared with 7% and 0%, respectively, in the bottom quartile." nature.com/articles/s4158…
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Nature Medicine
Nature Medicine@NatureMedicine·
In the Human Phenotype Project, home sleep apnea testing data was collected for a total of 16,812 nights in 6,410 individuals, allowing for a comprehensive study of the association of sleep traits with physiological features across 16 body systems. nature.com/articles/s4159…
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Eran Segal
Eran Segal@segal_eran·
Our lab at the Weizmann Institute was hit tonight by Iran We will rebuild and return 💪
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Guy Lutsker
Guy Lutsker@GLutsker·
In other words, those ranked by GluFormer as “high risk” truly did have worse outcomes long-term. Meanwhile, ranking based on blood A1C% alone showed no significant separation. It seems that GluFormer may add a layer of predictive power beyond standard lab measures.
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Guy Lutsker
Guy Lutsker@GLutsker·
We have a new and revised GluFormer manuscript! We expanded our analyses considerably: now showing that our AI model for CGM can identify individuals at higher risk of declining glycemic control before it happens, and can predict long-term diabetes & cardiovascular mortality.
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Guy Lutsker
Guy Lutsker@GLutsker·
Check out NVIDIA's blog post about our recent model, GluFormer
NVIDIA AI Developer@NVIDIAAIDev

🍪 A new #generativeAI model can now help diabetics predict glucose levels, and help answer their question, “How will eating this affect my glucose levels?” Researchers from the Weizmann Institute of Science, and Tel Aviv-based startup Pheno AI worked with us to develop GluFormer, an AI model that can predict an individual’s future glucose levels and other health metrics based on past glucose monitoring data. 📊🍎 blogs.nvidia.com/blog/ai-resear… #WorldDiabetesDay

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Yoad Tewel
Yoad Tewel@YoadTewel·
🚀 Excited to release the code and demo for ConsiStory, our #SIGGRAPH2024 paper! No fine-tuning needed — just fast, subject-consistent image generation! Check it out here 👇 Code: github.com/NVlabs/consist… Demo: build.nvidia.com/nvidia/consist…
AK@_akhaliq

Nvidia presents ConsiStory Training-Free Consistent Text-to-Image Generation paper page: huggingface.co/papers/2402.03… enable Stable Diffusion XL (SDXL) to generate consistent subjects across a series of images, without additional training.

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Keşfet

@WeizmannScience @Pheno_AI @Nature @mbzuai @nvidia @smadarshilo @nastya_godneva @ericxing