Showing 401 - 420 results of 33,274 for search '(explainer OR explained)', query time: 0.16s Refine Results
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    Postpartum depression risk prediction using explainable machine learning algorithms by Xudong Huang, Lifeng Zhang, Chenyang Zhang, Jing Li, Chenyang Li

    Published 2025-08-01
    “…This study aimed to develop an explainable machine learning model to predict the risk of PPD and to identify its key predictive factors.MethodsA retrospective analysis was conducted on 1,065 women who attended their 6-week postpartum follow-up visit at a tertiary maternal and child healthcare hospital in Shenyang, China, from January to December 2021. …”
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    Regulation of Immune Cell Infiltration into the CNS by Regional Neural Inputs Explained by the Gate Theory by Yasunobu Arima, Daisuke Kamimura, Lavannya Sabharwal, Moe Yamada, Hidenori Bando, Hideki Ogura, Toru Atsumi, Masaaki Murakami

    Published 2013-01-01
    “…Interestingly, this gateway is regulated by regional neural stimulations that can be mechanistically explained by the gate theory. In this review, we also discuss this theory and its potential for treating human diseases.…”
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    Unitarity triangle angles explained: a predictive new quark mass matrix texture by P. F. Harrison, W. G. Scott

    Published 2025-07-01
    “…We identify two novel symmetries of these mass matrices which explain the phenomenologically-successful relations α ≡ ϕ 2 ≃ π 2 $$ \frac{\pi }{2} $$ and β ≡ ϕ 1 ≃ π 8 $$ \frac{\pi }{8} $$ .…”
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  7. 407

    Differences in the force exerted during wrist movements are explained by a general mathematical model by Camilo Leonardo Sandoval Rodriguez, Carlos Julio Arizmendi Pereira, Diana María Reyes Bravo, Omar Lengerke, Ricardo Palacio, Andrés Jiménez Quezada

    Published 2024-12-01
    “…The results showed high R2 values (median 0.9) and significant random effects, indicating that sEMG signals can explain variations in force signals during different hand movements by introducing the type of movement as part of the random effects of the model. …”
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  8. 408

    Large Variations in HIV-1 Viral Load Explained by Shifting-Mosaic Metapopulation Dynamics. by Katrina A Lythgoe, François Blanquart, Lorenzo Pellis, Christophe Fraser

    Published 2016-10-01
    “…Notably, and in contrast to previous models, this new model can explain the large differences in set-point viral load (SPVL) observed between patients and their distribution, as well as the relatively low proportion of cells infected at any one time, and alters the predicted determinants of viral load variation.…”
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  9. 409

    How the HESS J1731-347 object could be explained using K− condensation by M. Veselský, P.S. Koliogiannis, V. Petousis, J. Leja, Ch.C. Moustakidis

    Published 2025-01-01
    “…To the best of our knowledge, this represents a first alternative attempt aimed to explain the bulk properties of the specific object with the inclusion of a kaon condensation in dense nuclear matter. …”
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  10. 410

    Mars's Crustal and Volcanic Structure Explained by Southern Giant Impact and Resulting Mantle Depletion by K. W. Cheng, A. B. Rozel, G. J. Golabek, H. A. Ballantyne, M. Jutzi, P. J. Tackley

    Published 2024-03-01
    “…Previous giant impact models coupled with simulations of mantle convection have shown that the crustal dichotomy can be explained by post‐impact melt crystallization that emplaced a thick crust in the southern hemisphere. …”
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    Probabilistic ranking of plant cultivars: stability explains differences from mean rank by Shayan Tohidi, Sigurdur Olafsson

    Published 2025-03-01
    “…The results from applying this method to data observed from multiple crops, namely, rapeseed, sorghum and maize, show that a) existing stability measures explain most of the differences, b) no stability measure explains all differences for all data, and c) stability measures that combine mean with specific type of stability perform the most like probabilistic order. …”
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    Dissolved Oxygen Modeling by a Bayesian-Optimized Explainable Artificial Intelligence Approach by Qiulin Li, Jinchao He, Dewei Mu, Hao Liu, Shicheng Li

    Published 2025-01-01
    “…To this end, the present study contributes a Bayesian-optimized explainable machine learning (ML) model to reveal DO dynamics and predict DO concentrations. …”
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