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40 ta ish

Ish: Optimizing Artificial Intelligence-aided breast cancer models: An empirical analysis of binary classifiers and regression-based feature selectors

  1. A review on image-based approaches for breast cancer detection, segmentation, and classification

    Zahra Rezaei

    Sharh maqola20213 iqtibos
    ABI

  2. A curated mammography data set for use in computer-aided detection and diagnosis research

    Rebecca Sawyer Lee, Francisco Javier Giménez Fuentes‐Guerra, Assaf Hoogi +3

    Maqola20173 iqtibos
    ABI

  3. Enhancing Prostate Cancer Classification by Leveraging Key Radiomics Features and Using the Fine-Tuned Linear SVM Algorithm

    Metin Varan, Jahongir Azimjonov, Bilgen Maçal

    MaqolaRadiomics and Machine Learning in Medical ImagingIEEE Access20232 iqtibos
    ABI

  4. Stochastic gradient descent classifier-based lightweight intrusion detection systems using the efficient feature subsets of datasets

    Jahongir Azimjonov, Taehong Kim

    Maqola20232 iqtibos
    ABI

  5. Breast cancer detection using deep learning: Datasets, methods, and challenges ahead

    Nusrat Mohi Ud Din, Rayees Ahmad Dar, Muzafar Rasool +1

    Sharh maqola20222 iqtibos
    ABI

  6. Computer-aided breast cancer detection and classification in mammography: A comprehensive review

    Kosmia Loizidou, Rafaella Elia, Costas Pitris

    Sharh maqola20232 iqtibos
    ABI

  7. Artificial Intelligence in Healthcare: Review, Ethics, Trust Challenges & Future Research Directions

    Pranjal Kumar, Siddhartha Chauhan, Lalit Kumar Awasthi

    Maqola20232 iqtibos
    ABI

  8. Detection and classification of breast cancer using logistic regression feature selection and GMDH classifier

    Ziba Khandezamin, Marjan Naderan, Mohammad Javad Rashti

    Maqola20202 iqtibos
    ABI

  9. Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review

    Jun Bai, Russell Posner, Tianyu Wang +2

    Sharh maqola20212 iqtibos
    ABI

  10. A Comprehensive Empirical Analysis of Data Sets, Regression-Based Feature Selectors, and Linear SVM Classifiers for Intrusion Detection Systems

    Jahongir Azimjonov, Taehong Kim

    MaqolaNetwork Security and Intrusion DetectionIEEE Internet of Things Journal20241 iqtibos
    ABI

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