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32 та иш

Иш: Machine learning estimation and optimization for evaluation of pharmaceutical solubility in supercritical carbon dioxide for improvement of drug efficacy

  1. Random Forests

    Leo Breiman

    Мақола200167 иқтибос
    ABI

  2. The Whale Optimization Algorithm

    Seyedali Mirjalili, Andrew Lewis

    Мақола20169 иқтибос
    ABI

  3. Greedy function approximation: A gradient boosting machine.

    Jerome H. Friedman

    Мақола20016 иқтибос
    ABI

  4. Gradient boosting machines, a tutorial

    Alexey Natekin, Alois Knoll

    Мақола20136 иқтибос
    ABI

  5. Random Forests

    Adele Cutler, D. Richard Cutler, John R. Stevens

    Боб20126 иқтибос
    ABI

  6. RANDOM FORESTS FOR CLASSIFICATION IN ECOLOGY

    D. Richard Cutler, Thomas C. Edwards, Karen H. Beard +4

    Мақола20075 иқтибос
    ABI

  7. Isolation Forest

    Fei Tony Liu, Kai Ming Ting, Zhi‐Hua Zhou

    Мақола20084 иқтибос
    ABI

  8. Ensemble Methods in Machine Learning

    Thomas G. Dietterich

    Боб20004 иқтибос
    ABI

  9. Supercritical carbon dioxide utilization in drug delivery: Experimental study and modeling of paracetamol solubility

    Hamidreza Bagheri, Behrouz Notej, Sara Shahsavari +1

    Мақола20223 иқтибос
    ABI

  10. Experimental solubility measurement of cephalexin in supercritical carbon dioxide

    Safar Ali Shojaee, Hamid Rajaei, Ali Zeinolabedini Hezave +2

    Мақола20133 иқтибос
    ABI

  11. Medium Gaussian SVM, Wide Neural Network and stepwise linear method in estimation of Lornoxicam pharmaceutical solubility in supercritical solvent

    Tao Wang, Chia‐Hung Su

    Мақола20213 иқтибос
    ABI

  12. RETRACTED: Prediction of busulfan solubility in supercritical CO2 using tree-based and neural network-based methods

    Zhou Tianhao, Hasan Sh. Majdi, Dmitry Olegovich Bokov +6

    Мақола20223 иқтибос
    ABI

  13. Machine learning aided drug development: Assessing improvement of drug efficiency by correlation of solubility in supercritical solvent for nanomedicine preparation

    Mohammed Ghazwani, M. Yasmin Begum

    Мақола20233 иқтибос
    ABI

  14. Random Forest: A Review

    Computer Science & Engineering &GZSCCET Bhatinda, Punjab, India, Eesha Goel, Er. Abhilasha +1

    Шарҳ мақола20173 иқтибос
    ABI

  15. Multi support vector models to estimate solubility of Busulfan drug in supercritical carbon dioxide

    Zhiyu Zhao, Peng Liu, Yijie Li +4

    Мақола20222 иқтибос
    ABI

  16. Machine learning model for prediction of drug solubility in supercritical solvent: Modeling and experimental validation

    Feifei An, Biju Theruvil Sayed, Rosario Mireya Romero‐Parra +8

    Мақола20222 иқтибос
    ABI

  17. Advancing nanomedicine production via green method: Modeling and simulation of pharmaceutical solubility at different temperatures and pressures

    Hanyi Song, Hua Shao, Ying Zhang +1

    Мақола20242 иқтибос
    ABI

  18. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI

  19. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI

  20. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI

  21. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI

  22. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI

  23. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI

  24. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI

  25. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI