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9 ta ish

Ish: Application of ensemble machine learning methods for diabetes diagnosis

  1. The task of assessing the risk in the operation of a complex free formal system

    Zafar Abdullaev, D Sh Ziyadullaev, D.T. Muhamediyeva

    MaqolaAdvanced Data Processing TechniquesJournal of Physics Conference Series20224 iqtibos
    ABI

  2. The worldwide epidemiology of type 2 diabetes mellitus—present and future perspectives

    Lei Chen, Dianna J. Magliano, Paul Zimmet

    Sharh maqola20114 iqtibos
    ABI

  3. Efficient Detection of DDoS Attacks Using a Hybrid Deep Learning Model with Improved Feature Selection

    Daniyal Alghazzawi, Omaimah Bamasag, Hayat Ullah +1

    Maqola20213 iqtibos
    ABI

  4. Implementing Machine Learning in Health Care — Addressing Ethical Challenges

    Danton Char, Nigam H. Shah, David Magnus

    Maqola20183 iqtibos
    ABI

  5. Deep learning for healthcare: review, opportunities and challenges

    Riccardo Miotto, Fei Wang, Shuang Wang +2

    Sharh maqola20173 iqtibos
    ABI

  6. Generalized models of a production system of fuzzy conclusion

    Davron Ziyadullaev, Dilnoz Muhamediyeva, Zafar Abdullaev +2

    MaqolaAdvanced Data Processing TechniquesE3S Web of Conferences20233 iqtibos
    ABI

  7. [Retracted] Classification of Diabetes Using Photoplethysmogram (PPG) Waveform Analysis: Logistic Regression Modeling

    Yousef Qawqzeh, Abdullah Bajahzar, Mahdi Jemmali +2

    Maqola20202 iqtibos
    ABI

  8. Applying deep neural networks for user intention identification

    Asad Masood Khattak, Anam Habib, Muhammad Zubair Asghar +3

    Maqola20202 iqtibos
    ABI

  9. A Hybrid Deep Learning Technique for Personality Trait Classification From Text

    Hussain Al-Ahmad, Muhammad Zubair Asghar, Muhammad Zubair Asghar +2

    Maqola20212 iqtibos
    ABI