NeuroQA is a large-scale 3D brain MRI visual question answering benchmark with verified image-grounded QA pairs, multi-domain coverage, and baseline evaluations showing current models lag behind text-only performance.
Alzheimer’s disease neuroimaging initiative (adni) clinical characterization.Neurology, 74(3):201–209
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NIAgent is a multi-agent system using code-centric execution and hierarchical verification to autonomously build and adapt neuroimaging analysis workflows, showing better predictive performance than standard pipelines on ADHD-200 and ADNI data.
Pan-FM learns balanced representations across seven organs by adaptively masking dominant organs during pre-training, yielding stronger disease prediction and missing-organ robustness than single-organ or naive multimodal baselines on UK Biobank.
citing papers explorer
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NeuroQA: A Large-Scale Image-Grounded Benchmark for 3D Brain MRI Understanding
NeuroQA is a large-scale 3D brain MRI visual question answering benchmark with verified image-grounded QA pairs, multi-domain coverage, and baseline evaluations showing current models lag behind text-only performance.
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Towards a Virtual Neuroscientist: Autonomous Neuroimaging Analysis via Multi-Agent Collaboration
NIAgent is a multi-agent system using code-centric execution and hierarchical verification to autonomously build and adapt neuroimaging analysis workflows, showing better predictive performance than standard pipelines on ADHD-200 and ADNI data.
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Pan-FM: A Pan-Organ Foundation Model with Saliency-Guided Masking for Missing Robustness
Pan-FM learns balanced representations across seven organs by adaptively masking dominant organs during pre-training, yielding stronger disease prediction and missing-organ robustness than single-organ or naive multimodal baselines on UK Biobank.