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  1. 1661

    Population FBA predicts metabolic phenotypes in yeast. by Piyush Labhsetwar, Marcelo C R Melo, John A Cole, Zaida Luthey-Schulten

    Published 2017-09-01
    “…We find the partitioning of flux between fermentation and respiration predicted by our model agrees with recent 13C fluxomics experiments, and that our model largely recovers the Crabtree effect (the experimentally known bias among certain yeast species toward fermentation with the production of ethanol even in the presence of oxygen), while FBA without proteomics constraints predicts respirative metabolism almost exclusively. …”
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  2. 1662

    STEP-BY-STEP PREDICTION OF LATE SPONTANEOUS MISCARRIAGE by Юлия Алексеевна Дударева, Татьяна Викторовна Раченкова, Сергей Вадимович Дронов

    Published 2025-05-01
    “…The aim of the study was to develop a step-by-step system for predicting late spontaneous miscarriages, taking into account clinical, anamnestic, echographic data, and the cytokine status of pregnant women. …”
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  3. 1663

    Prediction models for COVID-19 disease outcomes by Cynthia Y. Tang, Cheng Gao, Kritika Prasai, Tao Li, Shreya Dash, Jane A. McElroy, Jun Hang, Xiu-Feng Wan

    Published 2024-12-01
    “…Using the Virus-Human Outcomes Prediction (ViHOP) algorithm, we aim to utilize the individual’s clinical characteristics, the individual’s location, and the infecting SARS-CoV-2 virus characteristics obtained by whole genome sequencing to determine their likelihood of admission to the hospital, admission to the intensive care unit (ICU), or experiencing long COVID. …”
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  4. 1664

    Smart diabetes management: remote monitoring and predictive health insights by K.S. Smelyakov, I.A. Lurin, K.V. Misiura, A.S. Chupryna, T.V. Tyzhnenko, O.D. Dolhanenko, V.M. Repikhov

    Published 2025-06-01
    “…The use of deep learning and neural network algorithms enhances the accuracy of these predictions by capturing complex data trends over time. …”
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    Prediction of 1-year post-operative mortality in elderly patients with fragility hip fractures in China: evaluation of risk prediction models by Qiyuan Lu, Mengmeng Chen, Houfu Ling

    Published 2025-06-01
    “…This investigation conducts a comparative evaluation of seven prognostic models—the Sernbo Score, Jiang et al. model, Nottingham Hip Fracture Score (NHFS), Holt et al. algorithm, HEMA, ASAgeCoGeCC Score, and SHiPS—HiPSe, and SHire, and SHim, HEMA, ham Hip Fracture Score (mortality risk prediction in elderly fragility hip fracture patientsMethodsIn this retrospective cohort analysis, all consecutive patients aged isk prediction in elderly fragility hip fracture between January 2018 and October 2022 were enrolled. …”
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  9. 1669

    An Adaptive Maximum Power Output Sustaining System for a Photovoltaic Power Plant Based on a Robust Predictive Control Approach by I. Elzein, Yu. N. Petrenko

    Published 2020-10-01
    “…This paper makes an emphasis on model predictive controller as a control method for controlling the maximum power point tracking through the utilization of the well-known algorithm namely the Perturb and Observe technique. …”
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    Application of log-based specific surface area prediction for permeability modeling in a highly heterogeneous carbonate reservoir in the middle east by Mojtaba Homaie, Ida Lykke Fabricius, Morten Leth Hjuler, Asadollah Mahboubi, Ali Kadkhodaie, Reza Moussavi Harami

    Published 2025-08-01
    “…This study evaluates two log-based methodologies for specific surface modeling and their role in predicting permeability. The first method utilizes density and gamma-ray logs, as previously validated in North Sea chalks, while the second method innovatively integrates deep resistivity and porosity data using a K-nearest neighbor machine learning algorithm. …”
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    Cutting-edge approaches to specific energy prediction in TBM disc cutters: Integrating COSSA-RF model with three interpretative techniques by Jian Zhou, Zijian Liu, Chuanqi Li, Kun Du, Haiqing Yang

    Published 2025-06-01
    “…Therefore, in this paper, the sparrow search algorithm (SSA), combined with six chaotic mapping strategies, is utilized to optimize the random forest (RF) model for predicting SE, referred to as the COSSA-RF prediction models. …”
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    Solar Irradiance Prediction Method for PV Power Supply System of Mobile Sprinkler Machine Using WOA-XGBoost Model by Dan Li, Jiwei Qu, Delan Zhu, Zheyu Qin

    Published 2024-11-01
    “…The relation between meteorological parameters and solar irradiance is studied, and four different parameter combinations are formed and considered as inputs to the prediction model. Based on meteorological data provided by ten typical radiation stations uniformly distributed nationwide, an Extreme Gradient Boosting (XGBoost) model optimized using the Whale Optimization Algorithm (WOA) is developed to predict solar radiation. …”
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