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Can we explain machine learning-based prediction for rupture status assessments of intracranial aneurysms?

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第一作者： N,Mu

第一单位： Biomedical Engineering, Michigan Technological University, Houghton, MI, United States of America.

作者： N,Mu ^[1] ; M,Rezaeitaleshmahalleh ^[1] ; Z,Lyu ^[1] ; M,Wang ^[2] ; J,Tang ^[3] ; C M,Strother ^[4] ; J J,Gemmete ^[5] ; A S,Pandey ^[6] ; J,Jiang ^[7]

作者单位： Biomedical Engineering, Michigan Technological University, Houghton, MI, United States of America. ^[1] Department of Management Science and Statistics, The University of Texas at San Antonio, San Antonino, TX, United States of America. ^[2] Department of Health Administration and Policy, George Mason University, Fairfax, VA, United States of America. ^[3] Department of Radiology, University of Wisconsin, Madison, WI, United States of America. ^[4] Department of Radiology, University of Michigan, Ann Arbor, MI, United States of America. ^[5] Department of Neurosurgery, University of Michigan, Ann Arbor, MI, United States of America. ^[6] Biomedical Engineering, Michigan Technological University, Houghton, MI, United States of America.;Center for Biocomputing and Digital Health, Health Research Institute and Institute of Computing and Cybernetics, Michigan Technological University, Houghton, MI, United States of America. ^[7]

关键词 computational fluid dynamics intracranial aneurysm machine learning

医学主题词人类(Humans);颅内动脉瘤(Intracranial Aneurysm);贝叶斯定理(Bayes Theorem);算法(Algorithms)

DOI 10.1088/2057-1976/acb1b3

PMID 36626819

发布时间 2026-03-07

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准确一般字义偏差语意偏离译文作用小提交