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Integrating machine learning for advanced analysis of bioelectrical impedance parameters in children with nephrotic syndrome

• Authors : Quist, Josephine Reinert; Ward, Leigh C.; Jødal, Lars

Subjects: bioelectrical impedance; children; electric capacitance

• Source: Quist, J R, Ward, L C, Jødal, L, Andersen, R F, Hvas, C L & Brantlov, S 2026, 'Integrating machine learning for advanced analysis of

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Electromechanical Impedance Sensing Under Humid Conditions:Experimental Insights and Compensation Using Machine Learning

• Authors : Dahl, Mads Kofod; Hire, Jaamac Hassan; Zamani, Milad

Subjects: CNN; electro mechanical impedance; EMI

• Source: Dahl, M K, Hire, J H, Zamani, M, Luca, A & Moradi, F 2026, 'Electromechanical Impedance Sensing Under Humid Conditions : Experimental Insights and Compensation Using

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Developing and Assessing the Performance of a Machine Learning Model for Analyzing Drinking Behaviors in Minipigs for Experimental Research

• Authors : Deutch, Frederik; Hansen, Lars Schmidt; Saleh, Firas Omar

Subjects: animal welfare; drinking behavior; experimental animals

• Source: Deutch, F, Hansen, L S, Saleh, F O, Weiss, M G, Figueiredo, C, Moers, C, Keller, A K & Wagner, S R 2026, 'Developing and Assessing the Performance of a Machine

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Spatiotemporal modeling of annual diffuse flow-weighted total phosphorus concentrations in Danish headwater streams with machine learning

• Authors : Kronvang, Brian; Windolf, Jørgen; Tornbjerg, Henrik

• Source: Kronvang, B, Windolf, J, Tornbjerg, H, Frederiksen, R R & Larsen, S E 2026, 'Spatiotemporal modeling of annual diffuse flow-weighted total phosphorus concentrations in Danish headwater streams with

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Fast and Interpretable Machine Learning Modeling of Atmospheric Molecular Clusters

• Authors : Seppäläinen, Lauri; Kubečka, Jakub; Elm, Jonas

• Source: Seppäläinen, L, Kubečka, J, Elm, J & Puolamäki, K R 2026, 'Fast and Interpretable Machine Learning Modeling of Atmospheric Molecular

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A computational study for batch-Level diagnostics in industrial extrusion using interpretable machine learning and counterfactual analysis

• Authors : Nielsen, Mads Kjærgaard; Mikkelsen, Jacob

Subjects: Extrusion processing; Batch optimization; Industrial artificial intelligence

• Source: Nielsen, M K & Mikkelsen, J 2026, 'A computational study for batch-Level diagnostics in industrial extrusion using interpretable machine

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Integrating machine learning techniques for critical node identification in complex networks

• Authors : ReddyPriya, Madupuri; Enduri, Murali Krishna; Hajarathaiah, Koduru

Subjects: Centrality; Complex networks; Machine learning

• Source: ReddyPriya, M, Enduri, M K, Hajarathaiah, K, Satish, A & Bandaru, N 2026, 'Integrating machine learning techniques for critical node

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Machine learning and logistic regression in estimating survival in patients with high-malignant deep-seated soft tissue sarcomas:development and analysis based on a population-based retrospective cohort

• Authors : Thorn, Andrea; Lavery, Jessica A; Baad-Hansen, Thomas

Subjects: Humans; Sarcoma/mortality; Retrospective Studies

• Source: Thorn, A, Lavery, J A, Baad-Hansen, T, Forsberg, J A, Petersen, M M & Holm, C E 2026, 'Machine learning and logistic regression in

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A Machine Learning Application to Camera-Traps:Robust Species Interactions Datasets for Analysis of Mutualistic Networks

• Authors : Villalva, Pablo; Jordano, Pedro

• Source: Villalva, P & Jordano, P 2026, 'A Machine Learning Application to Camera-Traps : Robust Species Interactions Datasets for Analysis of

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Interpretable machine learning framework for air quality prediction in Istanbul using Shapley additive explanations (SHAP)

• Authors : Birinci, Enes; Ekmekcioğlu, Ömer; Ozdemir, Hüseyin

Subjects: Machine learning; PM; SHAP

• Source: Birinci, E, Ekmekcioğlu, Ö, Ozdemir, H & Deniz, A 2026, 'Interpretable machine learning framework for air quality prediction in Istanbul

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