Guy Lutsker

PhD student at the Weizmann Institute of Science

[Eran Segal @segal_eran]

Our new preprint is a significant milestone for us

We built "HealthFormer" by training on our deeply phenotyped cohort from the Human Phenotype Project data. Healthformer is a multimodal generative transformer model that tokenizes each participant's physiological trajectory across 667 modalities (biomarkers, body comp, sleep, CGM, microbiome, wearables, meds) and is trained with a single objective: predict the next measurement

Forecasting, risk stratification, and intervention-conditioned simulation all arise as queries from one shared representation

Key findings:

→ Matches direction of effect in 41/41 published RCTs; 30/41 within the reported 95% CI

→ Reconstructs biomarkers at r > 0.9; forecasts 2 yrs ahead

→ Validation on external data from UK Biobank, NHANES, PNP3, Framingham

→ Outperforms Framingham CVD & PREVENT-ASCVD on 27/30 endpoints

→ Predicts individual 6-mo responses in a held-out RCT

Paper: https://t.co/Y82xI9U5hn

Great work by Guy Lutsker, Gal Sapir, Jordi Merino, Smadar Shilo, Anastasia Godneva, Eli Meirom, Shie Mannor, Hagai Rossman, Gal Chechik

[Eran Segal @segal_eran]

Our new preprint on a gait foundation model that we developed from videos of over 3,400 people walking and doing other motor tasks. This 3D skeletal motion model can predict diverse human traits and disease conditions

https://t.co/g5Nfqq5U0e

[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:
https://t.co/8Y5auU36nD
https://t.co/N3rFkPRVbg

Great work by Evandro Ortigossa and @GLutsker

[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

[nature @Nature]

Nature research paper: A foundation model for continuous glucose monitoring data

https://t.co/NLOo2gLYJp

[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.

📄 https://t.co/LhjRF0GB6H

[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: https://t.co/SrdxDzftYU

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

[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."
https://t.co/4etmTh93wI

[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. https://t.co/Ay8CJtcFDF

[Eran Segal @segal_eran]

Our lab at the Weizmann Institute was hit tonight by Iran

We will rebuild and return 💪

[Guy Lutsker @GLutsker]

Check out our previous thread about GluFormer, with link to the ArXiv manuscript:
https://t.co/T8qgfhLCNW

[Guy Lutsker @GLutsker]

Thrilled to share our work, GluFormer: A foundation model for continuous glucose monitoring (CGM) data, trained on over 10 million measurements from over 10,000 individuals.

Read the full paper here: https://t.co/pWt8IXRH7y.

1/8

[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.

[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.

[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. 📊🍎

https://t.co/BvICE4cWmL

#WorldDiabetesDay

[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: https://t.co/AojrWrSK5R
Demo: https://t.co/FzRWvGRrE4