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Foundation Model

All articles tagged with #foundation model

technology21 days ago•35 min saved

Prima: a health-system-scale MRI foundation model reshaping neuroimaging

A team trains Prima, a health-system-scale AI foundation model for MRI, using over 220,000 studies. In a one-year, system-wide study (29,431 MRIs across 52 neurologic diagnoses), Prima achieves a mean AUC of 92.0%, outperforming state-of-the-art models, and offers explainable predictions, radiologist worklist prioritization, and clinical referral recommendations. The model demonstrates algorithmic fairness across sensitive groups and leverages a hierarchical ViT with a VQ-VAE-based volume tokenizer and CLIP objective, aided by LLM-assisted report summarization. Data originates from the University of Michigan with MIT-licensed code; data sharing is governed by IRB and institutional agreements. Overall, the work showcases health system-scale AI training as a pathway to faster, fairer AI-driven neuroimaging in clinical care.

via Nature|

#fairness #foundation-model #health-system-scale

technology1 month ago•20 min saved

GluFormer: A universal model for decoding glucose patterns across diverse populations

Researchers introduce GluFormer, a self-supervised, autoregressive foundation model trained on over 10 million CGM measurements to learn transferable glucose representations across 19 external cohorts spanning 5 countries and multiple devices. The learned representations improve forecasting of glycemic metrics, stratify prediabetes progression better than baseline HbA1c, and identify higher long-term diabetes and cardiovascular mortality risk than HbA1c in follow-up data. A multimodal extension incorporating dietary data can simulate plausible glucose trajectories and predict individual glycemic responses to food, suggesting GluFormer as a generalizable tool to advance precision metabolic health.

via Nature|

#continuous-glucose-monitoring #foundation-model #glucose-monitoring

health-and-medicine1 month ago•54 min saved

AI Model Uses Sleep Data to Predict Long-Term Disease Risks

The article introduces SleepFM, a large-scale foundation model trained on over 585,000 hours of sleep data from 65,000+ participants, which captures complex sleep physiology across multiple modalities and demonstrates strong predictive power for a wide range of diseases, outperforming traditional models and showing robust generalization across datasets and time.

via Nature|

#deep-learning #disease-prediction #foundation-model