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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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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A hybrid machine learning and centrality framework for key node identification in complex networks

Authors : Madupuri, Reddy Priya; Enduri, Murali Krishna; Sobin, C. C.

Subjects: Complex networks; Critical Vertices; Global centrality measures

Source: Madupuri, R P, Enduri, M K, Sobin, C C, Koduru, H & Bandaru, N 2026, 'A hybrid machine learning and centrality framework for key node

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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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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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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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Predicting DNA Origami Stability in Physiological Media by Machine Learning

Authors : Zubia-Aranburu, Judith; Gardin, Andrea; Paffen, Lars

Subjects: diffusion coefficient; DNA origami; dynamic light scattering

Source: Zubia-Aranburu, J, Gardin, A, Paffen, L, Tollemeto, M, Alberdi, A, Termenon, M, Grisoni, F & Patiño Padial, T 2026, 'Predicting DNA Origami Stability in Physiological Media by

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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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Incorporating Qualitative Metrics into a Computational Model Using Machine Learning

Authors : Kærsaa, Laura; Kirkegaard, Poul Henning

Subjects: Tectonic design; Aesthetic Metrics; Computational architecture

Source: Kærsaa, L & Kirkegaard, P H 2025, 'Incorporating Qualitative Metrics into a Computational Model Using Machine Learning', International

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Emulation of Variational Quantum Circuits on Embedded Systems for Real-Time Quantum Machine Learning Applications

Authors : Masoudian, Ali; Jakobsen, Uffe; Khooban, Mohammad Hassan

Subjects: FPGA; industrial design; online training

Source: Masoudian, A, Jakobsen, U & Khooban, M H 2025, 'Emulation of Variational Quantum Circuits on Embedded Systems for Real-Time Quantum Machine

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نتائج البحث

فلترة النتائج

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

Integrating machine learning techniques for critical node identification in complex networks

A hybrid machine learning and centrality framework for key node identification in complex networks

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

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

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

Predicting DNA Origami Stability in Physiological Media by Machine Learning

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

Incorporating Qualitative Metrics into a Computational Model Using Machine Learning

Emulation of Variational Quantum Circuits on Embedded Systems for Real-Time Quantum Machine Learning Applications

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