Teaching agentic AI to learn expert reasoning for rare disease diagnosis
LiteOdyssey: 一种用于可解释罕见病诊断的轻量级推理AI智能体
Minh-Ha Nguyen, Erica Gray, Bryce A. Schuler, Kevin W. Byram, Chih-Ting Yang, Fan Ma, Hua Xu, Wu-Chen Su, Chao Yan, Wei-Qi Wei, Adam Wright, Lisa Bastarache, Josh F. Peterson, Lingyao Li, Siyuan Ma, Undiagnosed Diseases Network, Rizwan Hamid, Thomas A. Cassini, Cathy Shyr
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Vanderbilt University(范德堡大学)
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Vanderbilt University Medical Center(范德堡大学医学中心)
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University of South Florida(南佛罗里达大学)
Verifiable abstention makes AI leak diagnosis accountable in water distribution networks
可验证弃权使AI在供水管网泄漏诊断中具备可问责性
Tianwei Mu, Yue Wang, Mingzhe Yuan, Manhong Huang, Wenhong Wang, Xuerui Yin, Qing Luo, Min Xiao, Hui Yang, Jun Li, Dan Xue
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School of Municipal Engineering and Environment, Shenyang Jianzhu University(沈阳建筑大学市政工程与环境学院)
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Guangzhou Institute of Industrial Intelligence(广州工业智能研究院)
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College of Environment, Shenyang University(沈阳大学环境学院)
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Shenyang Institute of Automation, Chinese Academy of Sciences(中国科学院沈阳自动化研究所)
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College of Environmental Science and Engineering, State Environmental Protection Engineering Center for Pollution Treatment and Control in Textile Industry, Donghua University(东华大学环境科学与工程学院(国家环境保护纺织污染防治工程技术中心))
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School of Information Science and Engineering, Shenyang University of Technology(沈阳工业大学信息科学与工程学院)
Comments42 pages, 5 main figures, 1 main table, 2 extended data figures, 3 supplementary figures, 15 supplementary tables. Code and data availability described in the paper
MIFR: A Modality-Invariant and Fair Representation Framework for Skin Disease Classification
MIFR:用于皮肤病分类的模态不变公平表示框架
Asonyu Senge Njih, Yvan Guifo Fodjo, Vianney Kengne Tchendji, Jerry Lacmou Zeutouo, Kerol Djoumessi
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University of Dschang(德昌大学)
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Université Paris-Panthéon-Assas(巴黎先贤祠-阿萨斯大学)
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Université de Picardie Jules Verne(儒勒·凡尔纳皮卡第大学)
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Hertie Institute for AI in Brain Health, University of Tübingen(蒂宾根大学赫蒂脑健康人工智能研究所)
CommentsCode and data: this https URL (https://github.com/1549080929-debug/math_agent) Keywords: LLM verification; verification autonomy; completeness; ground truth; trustworthy AI Writing and implementation assisted by an AI language model; all experiments, data, and research decisions are the author's own
CommentsThis paper was presented at 2025 10th International Conference on Applying New Technology in Green Buildings (ATiGB). Please cite the published version