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Работы, цитирующие эту работу

Работ: 8

Работа: <scp>YOLOv8</scp> Outperforms Traditional <scp>CNN</scp> Models in Mammography Classification: Insights From a Multi‐Institutional Dataset

  1. Advanced machine learning framework for enhancing breast cancer diagnostics through transcriptomic profiling

    Mohamed J. Saadh, Hanan Hassan Ahmed, Radhwan Abdul Kareem +11

    СтатьяGene expression and cancer classificationDiscover Oncology2025Цитирований: 0
    ABI

  2. Multi-objective deep learning for lung cancer detection in CT images: enhancements in tumor classification, localization, and diagnostic efficiency

    Abdulqader Faris Abdulqader, Shaymaa Mohammed Abdulameer, Ashok Kumar Bishoyi +10

    СтатьяLung Cancer Diagnosis and TreatmentDiscover Oncology2025Цитирований: 0
    ABI

  3. TabNet and TabTransformer: Novel Deep Learning Models for Chemical Toxicity Prediction in Comparison With Machine Learning

    Firas Mahmood Mustafa, Ali Fawzi Al‐Hussainy, Hardik Doshi +10

    СтатьяComputational Drug Discovery MethodsJournal of Applied Toxicology2025Цитирований: 0
    ABI

  4. Advanced feature fusion of radiomics and deep learning for accurate detection of wrist fractures on X-ray images

    Mohamed J. Saadh, Qusay Mohammed Hussain, Rafid Jihad Albadr +10

    СтатьяArtificial Intelligence in Healthcare and EducationBMC Musculoskeletal Disorders2025Цитирований: 0
    ABI

  5. A multi-center study of transformer-based CNNs for multiple sclerosis lesion segmentation on 3D FLAIR MRI

    Mohamed J. Saadh, Wajida Ataallah Khidr, Rafid Jihad Albadr +10

    СтатьяMultiple Sclerosis Research StudiesNeuroradiology2025Цитирований: 0
    ABI

  6. Reproducible meningioma grading across multi-center MRI protocols via hybrid radiomic and deep learning features

    Mohamed J. Saadh, Rafid Jihad Albadr, Dharmesh Sur +10

    СтатьяMeningioma and schwannoma managementNeuroradiology2025Цитирований: 0
    ABI

  7. Radiomics meets transformers: A novel approach to tumor segmentation and classification in mammography for breast cancer

    Mohamed J. Saadh, Qusay Mohammed Hussain, Rafid Jihad Albadr +10

    СтатьяRadiomics and Machine Learning in Medical ImagingJournal of X-Ray Science and Technology2025Цитирований: 0
    ABI

  8. Integrating histopathology and immune marker analysis for machine learning-based colorectal cancer prognostics

    Mohamed J. Saadh, Tamara Nazar Saeed, Karar H. Alfarttoosi +10

    СтатьяAI in cancer detectionDiagnostic Pathology2026Цитирований: 0
    ABI