activity
20232026
most citedFrom Glucose Patterns to Health Outcomes: A Generalizable Foundation Model for Continuous Glucose Monitor Data Analysis

10 citations · 14 across the 5 of their papers we have counts for

collaborators

6 papers

cs.AI2026

DoAtlas-2: A Foundation for Self-Evolving Causal Biomedical Discovery

Yulong Li, Rong Xia, Yuxuan Zhang +12

We introduce DoAtlas-2, a foundation for self-evolving causal biomedical discovery that organizes knowledge around causal mechanisms and advances through external evidence from hum…

cs.LG2026

PhenoBench: Mapping What a Deeply Phenotyped Human Cohort Can Tell Us

Gal Sapir, Alon Diament, Adva Wolf +7

Deeply phenotyped cohorts combine clinical, imaging, molecular, and wearable observations across timescales from seconds to years, but heterogeneous analyses are not directly compa…

cs.AI2026

Simulating clinical interventions with a generative multimodal model of human physiology

Guy Lutsker, Gal Sapir, Jordi Merino +7

Understanding how human health changes over time, and why responses to interventions vary between individuals, remains a central challenge in medicine. Here we present HealthFormer…

q-bio.QM2024★ 10 cited

From Glucose Patterns to Health Outcomes: A Generalizable Foundation Model for Continuous Glucose Monitor Data Analysis

Guy Lutsker, Gal Sapir, Smadar Shilo +11

Recent advances in SSL enabled novel medical AI models, known as foundation models, offer great potential for better characterizing health from diverse biomedical data. CGM provide…

cs.CV2024★ 2 cited

COMPRER: A Multimodal Multi-Objective Pretraining Framework for Enhanced Medical Image Representation

Guy Lutsker, Hagai Rossman, Nastya Godiva +1

Substantial advances in multi-modal Artificial Intelligence (AI) facilitate the combination of diverse medical modalities to achieve holistic health assessments. We present COMPRER…

cs.LG2023★ 2 cited

A Multimodal Dataset of 21,412 Recorded Nights for Sleep and Respiratory Research

Alon Diament, Maria Gorodetski, Adam Jankelow +5

This study introduces a novel, rich dataset obtained from home sleep apnea tests using the FDA-approved WatchPAT-300 device, collected from 7,077 participants over 21,412 nights. T…