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1 Ergebnisse
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A machine learning-derived gene signature for assessing rup..:
Taoyuan Lu
;
Yanyan He
;
Zaoqu Liu
...
https://www.frontiersin.org/articles/10.3389/fcvm.2023.1075584/full. , 2023
Link:
https://doi.org/10.3389/fcvm.2023.1075584
RT Journal T1 <Title>A machine learning-derived gene signature for assessing rupture risk and circulatory immunopathologic landscape in patients with intracranial aneurysms</Title> UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:ccf1ebd305e04a6f885543719c7076b0&Exemplar=1&LAN=DE A1 Taoyuan Lu A1 Yanyan He A1 Zaoqu Liu A1 Chi Ma A1 Song Chen A1 Rufeng Jia A1 Lin Duan A1 Chunguang Guo A1 Yiying Liu A1 Dehua Guo A1 Tianxiao Li A1 Yingkun He PB Frontiers Media S.A. YR 2023 K1 intracranial aneurysm K1 machine learning K1 multigene model K1 rupture risk K1 immunopathological features K1 precision medicine K1 Diseases of the circulatory (Cardiovascular) system K1 RC666-701 JF https://www.frontiersin.org/articles/10.3389/fcvm.2023.1075584/full LK http://dx.doi.org/https://doi.org/10.3389/fcvm.2023.1075584 DO https://doi.org/10.3389/fcvm.2023.1075584 SF ELIB - SuUB Bremen
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