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NeuroAgent uses LLM agents to automate neuroimaging analysis and research

Researchers have developed NeuroAgent, an LLM-driven framework designed to automate complex preprocessing and analysis for multimodal neuroimaging data. This system utilizes a hierarchical multi-agent architecture to generate, execute, and validate code for various imaging types like sMRI, fMRI, dMRI, and PET. Evaluations on a large dataset demonstrated NeuroAgent's capability to significantly reduce manual effort and enable end-to-end automated pipelines, achieving high accuracy in intent parsing and preprocessing correctness, with the strongest backend reaching 84.8% correctness. AI

影响 Automates complex neuroimaging analysis, potentially accelerating research and disease classification.

排序理由 This is a research paper detailing a new framework for neuroimaging analysis.

在 arXiv cs.AI 阅读 →

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NeuroAgent uses LLM agents to automate neuroimaging analysis and research

报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Lujia Zhong, Yihao Xia, Jianwei Zhang, Shuo huang, Jiaxin Yue, Mingyang Xia, Yonggang Shi ·

    NeuroAgent: LLM Agents for Multimodal Neuroimaging Analysis and Research

    arXiv:2605.06584v1 Announce Type: new Abstract: Multimodal neuroimaging analysis often involves complex, modality-specific preprocessing workflows that require careful configuration, quality control, and coordination across heterogeneous toolchains. Beyond preprocessing, downstre…

  2. arXiv cs.AI TIER_1 English(EN) · Yonggang Shi ·

    NeuroAgent: LLM Agents for Multimodal Neuroimaging Analysis and Research

    Multimodal neuroimaging analysis often involves complex, modality-specific preprocessing workflows that require careful configuration, quality control, and coordination across heterogeneous toolchains. Beyond preprocessing, downstream statistical analysis and disease classificati…