James Loftus

A New York University team released Neuro-JEPA, a multimodal foundation model that encodes T1w, T2w and FLAIR brain MRI contrasts in one architecture, pretrained on 1,551,862 scans from 428,647 studies. It outperformed BrainIAC, VoCo and NeuroVFM overall across 47 downstream tasks in three health systems and 12 public datasets while using less than one-third of NeuroVFM's pretraining data, and reached up to 15% higher few-shot AUROC on label-scarce tasks such as gliosis and multiple sclerosis, with roughly 15% on the NACC Alzheimer's disease task.

A New York University team released Neuro-JEPA, a multimodal foundation model that encodes T1w, T2w and FLAIR brain MRI contrasts in one architecture, pretrained on 1,551,862 scans from 428,647 studies. It outperformed BrainIAC, VoCo and NeuroVFM overall across 47 downstream tasks in three health systems and 12 public datasets while using less than one-third of NeuroVFM's pretraining data, and reached up to 15% higher few-shot AUROC on label-scarce tasks such as gliosis and multiple sclerosis, with roughly 15% on the NACC Alzheimer's disease task.