Showing 101 - 120 results of 43,723 for search '(( i ((large decrease) OR (large increases)) ) OR ( a ((largest decrease) OR (larger decrease)) ))', query time: 2.05s Refine Results
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    Supplementary Material for: Effects of White Matter Hyperintensities on 90-Day Functional Outcome after Large Vessel and Non-Large Vessel Stroke by Griessenauer C.J. (8965901)

    Published 2020
    “…<b><i>Material and Methods:</i></b> We reviewed acute ischemic stroke patients admitted between 2009 and 2017 at a large healthcare system in the USA. …”
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    Data_Sheet_1_Phenotypic Clumping Decreases With Flock Richness in Mixed-Species Bird Flocks.csv by Priti Bangal (9979259)

    Published 2021
    “…We examined the relationship between phenotypic clumping and flock richness using four variables—body size, foraging behavior, foraging height and taxonomic relatedness. Using a null model approach, we found that small flocks were more phenotypically clumped for body size than expected by chance; however, phenotypic clumping decreased as flocks increased in size and approached expected phenotypic variation in large flocks. …”
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    Data_Sheet_1_Decreased modular segregation of the frontal–parietal network in major depressive disorder.docx by Zhihui Lan (13135119)

    Published 2022
    “…Fifty-one MDD patients and forty-three matched healthy controls (HC) were recruited in the present study. …”
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    Decreased CNPase levels in the SG/RC in <i>Large</i><sup><i>myd/myd</i></sup> <i>mice</i>. by Shigefumi Morioka (8893511)

    Published 2020
    “…<p>Lysates were obtained from the spiral ganglion (SG)/Rosenthal’s canal (RC) of the P5-7 control and <i>Large</i><sup><i>myd/myd</i></sup> mice. CNPase immunoblotting showed decreased levels of CNPase in the <i>Large</i><sup><i>myd/myd</i></sup> mice. …”
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    S1 Dataset - by Rabia Asghar (18840759)

    Published 2024
    “…While WBC classification was originally rooted in conventional ML, there has been a notable shift toward the use of DL, and particularly convolutional neural networks (CNN), with 54.4% of identified studies (n = 74) including the use of CNNs, and particularly in concurrence with larger datasets and bespoke features e.g., parallel data pre-processing, feature selection, and extraction. …”
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