These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

127 related articles for article (PubMed ID: 39329567)

  • 1. Explainable Ensemble Learning and Multilayer Perceptron Modeling for Compressive Strength Prediction of Ultra-High-Performance Concrete.
    Aydın Y; Cakiroglu C; Bekdaş G; Geem ZW
    Biomimetics (Basel); 2024 Sep; 9(9):. PubMed ID: 39329567
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Application of Ensemble Machine Learning Methods to Estimate the Compressive Strength of Fiber-Reinforced Nano-Silica Modified Concrete.
    Anjum M; Khan K; Ahmad W; Ahmad A; Amin MN; Nafees A
    Polymers (Basel); 2022 Sep; 14(18):. PubMed ID: 36146051
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Interpretable Predictive Modelling of Basalt Fiber Reinforced Concrete Splitting Tensile Strength Using Ensemble Machine Learning Methods and SHAP Approach.
    Cakiroglu C; Aydın Y; Bekdaş G; Geem ZW
    Materials (Basel); 2023 Jun; 16(13):. PubMed ID: 37444890
    [TBL] [Abstract][Full Text] [Related]  

  • 4. In-Depth Analysis of Cement-Based Material Incorporating Metakaolin Using Individual and Ensemble Machine Learning Approaches.
    Bulbul AMR; Khan K; Nafees A; Amin MN; Ahmad W; Usman M; Nazar S; Arab AMA
    Materials (Basel); 2022 Nov; 15(21):. PubMed ID: 36363356
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Predicting compressive strength of high-performance concrete with high volume ground granulated blast-furnace slag replacement using boosting machine learning algorithms.
    Rathakrishnan V; Bt Beddu S; Ahmed AN
    Sci Rep; 2022 Jun; 12(1):9539. PubMed ID: 35680937
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Machine learning and interactive GUI for concrete compressive strength prediction.
    Elshaarawy MK; Alsaadawi MM; Hamed AK
    Sci Rep; 2024 Jul; 14(1):16694. PubMed ID: 39030283
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Compressive Strength Evaluation of Ultra-High-Strength Concrete by Machine Learning.
    Shen Z; Deifalla AF; Kamiński P; Dyczko A
    Materials (Basel); 2022 May; 15(10):. PubMed ID: 35629548
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Forecasting the strength of preplaced aggregate concrete using interpretable machine learning approaches.
    Javed MF; Fawad M; Lodhi R; Najeh T; Gamil Y
    Sci Rep; 2024 Apr; 14(1):8381. PubMed ID: 38600161
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Predicting the Compressive Strength of Sustainable Portland Cement-Fly Ash Mortar Using Explainable Boosting Machine Learning Techniques.
    Wang H; Ding Y; Kong Y; Sun D; Shi Y; Cai X
    Materials (Basel); 2024 Sep; 17(19):. PubMed ID: 39410316
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Ensemble Machine-Learning-Based Prediction Models for the Compressive Strength of Recycled Powder Mortar.
    Fei Z; Liang S; Cai Y; Shen Y
    Materials (Basel); 2023 Jan; 16(2):. PubMed ID: 36676320
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Compressive Strength Estimation of Steel-Fiber-Reinforced Concrete and Raw Material Interactions Using Advanced Algorithms.
    Khan K; Ahmad W; Amin MN; Ahmad A; Nazar S; Alabdullah AA
    Polymers (Basel); 2022 Jul; 14(15):. PubMed ID: 35956580
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A Risk Prediction Model for Physical Restraints Among Older Chinese Adults in Long-term Care Facilities: Machine Learning Study.
    Wang J; Chen H; Wang H; Liu W; Peng D; Zhao Q; Xiao M
    J Med Internet Res; 2023 Apr; 25():e43815. PubMed ID: 37023416
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Predictive Modeling of Mechanical Properties of Silica Fume-Based Green Concrete Using Artificial Intelligence Approaches: MLPNN, ANFIS, and GEP.
    Nafees A; Javed MF; Khan S; Nazir K; Farooq F; Aslam F; Musarat MA; Vatin NI
    Materials (Basel); 2021 Dec; 14(24):. PubMed ID: 34947124
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Comparison of Prediction Models Based on Machine Learning for the Compressive Strength Estimation of Recycled Aggregate Concrete.
    Khan K; Ahmad W; Amin MN; Aslam F; Ahmad A; Al-Faiad MA
    Materials (Basel); 2022 May; 15(10):. PubMed ID: 35629456
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Prediction of compressive strength of concrete based on improved artificial bee colony-multilayer perceptron algorithm.
    Li P; Zhang Y; Gu J; Duan S
    Sci Rep; 2024 Mar; 14(1):6414. PubMed ID: 38494524
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Forecasting the Mechanical Properties of Plastic Concrete Employing Experimental Data Using Machine Learning Algorithms: DT, MLPNN, SVM, and RF.
    Nafees A; Khan S; Javed MF; Alrowais R; Mohamed AM; Mohamed A; Vatin NI
    Polymers (Basel); 2022 Apr; 14(8):. PubMed ID: 35458331
    [TBL] [Abstract][Full Text] [Related]  

  • 17. On the Use of Machine Learning Models for Prediction of Compressive Strength of Concrete: Influence of Dimensionality Reduction on the Model Performance.
    Wan Z; Xu Y; Šavija B
    Materials (Basel); 2021 Feb; 14(4):. PubMed ID: 33546376
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Non-destructive test-based assessment of uniaxial compressive strength and elasticity modulus of intact carbonate rocks using stacking ensemble models.
    Fereidooni D; Karimi Z; Ghasemi F
    PLoS One; 2024; 19(6):e0302944. PubMed ID: 38857272
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Modeling strength characteristics of basalt fiber reinforced concrete using multiple explainable machine learning with a graphical user interface.
    Kulasooriya WKVJB; Ranasinghe RSS; Perera US; Thisovithan P; Ekanayake IU; Meddage DPP
    Sci Rep; 2023 Aug; 13(1):13138. PubMed ID: 37573410
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An ensemble learning-based prediction model for the compressive strength degradation of concrete containing superabsorbent polymers (SAP).
    Hosseinzadeh M; Mousavi SS; Dehestani M
    Sci Rep; 2024 Aug; 14(1):18535. PubMed ID: 39122829
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.