Showing 2,201 - 2,220 results of 2,900 for search '"(feature OR features) parameters (computation" OR computational")', query time: 0.26s Refine Results
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    Obtaining patient phenotypes in SARS-CoV-2 pneumonia, and their association with clinical severity and mortality by Fernando García-García, Dae-Jin Lee, Mónica Nieves-Ermecheo, Olaia Bronte, Pedro Pablo España, José María Quintana, Rosario Menéndez, Antoni Torres, Luis Alberto Ruiz Iturriaga, Isabel Urrutia, COVID-19 & Air Pollution Working Group

    Published 2024-06-01
    “…We proposed a sequence of machine learning stages: feature scaling, missing data imputation, reduction of data dimensionality via Kernel Principal Component Analysis (KPCA), and clustering with the k-means algorithm. …”
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    Reconstructing Fractional Holographic Dark Energy with scalar and gauge fields by Ayush Bidlan, Paulo Moniz, Oem Trivedi

    Published 2025-05-01
    “…In more detail, we methodically compute the corresponding Equation of State (EoS) parameters and field (kinetic and potential) features for the fractional parameter ( $$\alpha $$ α ) range, viz. $$1<\alpha \le 2$$ 1 < α ≤ 2 . …”
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    Spherical-deconvolution informed filtering of tractograms changes laterality of structural connectome by Yifei He, Yoonmi Hong, Ye Wu

    Published 2024-12-01
    “…Three typical tracking algorithms were used to construct the raw tractography, and two popular fiber filtering methods(SIFT and SIFT2) were employed to filter the tractography across a range of parameters. Laterality indices were computed for six popular biological features, including four microstructural measures (AD, FA, RD, and T1/T2 ratio) and two structural features (fiber length and connectivity) for each brain region. …”
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    Imaging‐Based Prediction of Ki‐67 Expression in Hepatocellular Carcinoma: A Retrospective Study by Chiyu Cai, Liancai Wang, Lianyuan Tao, Hengli Zhu, Yongnian Ren, Deyu Li, Dongxiao Li

    Published 2025-02-01
    “…Patients were categorized into high (> 20%) and low (≤ 20%) Ki‐67 expression groups based on cellular proliferation levels. Radiomic features were extracted from enhanced CT scans and combined with clinical parameters to develop a predictive model for Ki‐67 expression. …”
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